For the full video of this presentation, please visit:
https://www.embedded-vision.com/industry-analysis/video-interviews-demos/vision-opportunities-healthcare-presentation-woodside-capit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Rudy Burger, Managing Partner, and Vini Jolly, Executive Director, both of Woodside Capital Partners, deliver the presentation "Vision Opportunities in Healthcare" at the Embedded Vision Alliance's December 2019 Vision Industry and Technology Forum. Burger and Jolly outline trends and opportunities in computer vision for healthcare applications.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/industry-analysis/video-interviews-demos/potential-impacts-privacy-regulation-and-litigation-vision-
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Robert E. Cattanach, Partner at Dorsey & Whitney LLP, delivers the presentation "Potential Impacts of Privacy Regulation and Litigation on Vision Technology" at the Embedded Vision Alliance's December 2019 Vision Industry and Technology Forum. Cattanach provides insights into the fast-changing world of privacy regulation and litigation.
Ethical Considerations and Relation Centered Design for mHealth Applications Kate Michi Ettinger
Ethical Considerations and Relation Centered Design for mHealth Applications presented in the Medical Devices Track: Strategies for Successful Implementation of mHealth in Low Resource Settings chaired by Walter Karlen, PhD, Grand Challenges Canada grantee and post-doc at University of British Columbia and Stellenbosch University.
Presented June 6, 2014, at UNESCO Technology for Development 2014, theme: What is Essential?, hosted by EPFL and CODEV in Lausanne, Switzerland. For more information: http://wiki.epfl.ch/opentech4dev
Please Message To Request Copy of this Presentation for Download
AI in Healthcare: From Hype to Impact (updated)Mei Chen, PhD
The primary goal of this workshop is to help health professionals gain a critical understanding of the various types of AI technologies available so they can make wise decisions and invest AI for healthcare improvement.
Bio IT World 2019 - AI For Healthcare - Simon Taylor, LucidworksLucidworks
Presentation from Bio IT World, Boston | April 16-18, 2019
Track: AI for Healthcare: Practical Application of AI in Clinical Healthcare
Session Title: To AI or Not to AI, That Is the Question
Speaker: Simon Taylor, Lucidworks
AI in Health Care: How to Implement Medical Imaging using Machine Learning?Skyl.ai
About the webinar
According to a report “The Digital Universe Driving Data Growth in Healthcare,” published by EMC with research and analysis from IDC, Hospitals are producing 50 petabytes of data per year. Almost 90% of this data is comprised of medical imaging i.e. digital images from scans like MRIs or CTs. More than 97% of this data goes unanalyzed or unused.
The top healthcare institutions across the globe are adopting AI in medical imaging to increase speed and imaging accuracy, monitor data in real-time and eliminate the need for humans to do time-consuming and complex tasks. This has been enabling doctors to optimize treatment approaches, speed of care and interconnected health conditions.
Through this webinar, we will understand how AI can be used to automate routine processes and procedures and help radiologists to identify patterns, and help in treating patients with critical conditions quickly.
What you'll learn
- How healthcare institutions are leveraging AI to augment decision making, prevent medical errors, and reduce costs in medical imaging
- Discuss the approach to automate machine learning workflow, creating and deploying models in hours, not weeks or months
- Demo: How to detect pneumonia from chest x-rays using AI within a few minutes using skyl.ai
To explore more, visit: https://skyl.ai/form?p=start-trial
Algorithms and bias: What lenders need to knowWhite & Case
The algorithms that power fintech may discriminate in ways that can be difficult to anticipate—and financial institutions can be held accountable even when alleged discrimination is clearly unintentional.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/industry-analysis/video-interviews-demos/potential-impacts-privacy-regulation-and-litigation-vision-
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Robert E. Cattanach, Partner at Dorsey & Whitney LLP, delivers the presentation "Potential Impacts of Privacy Regulation and Litigation on Vision Technology" at the Embedded Vision Alliance's December 2019 Vision Industry and Technology Forum. Cattanach provides insights into the fast-changing world of privacy regulation and litigation.
Ethical Considerations and Relation Centered Design for mHealth Applications Kate Michi Ettinger
Ethical Considerations and Relation Centered Design for mHealth Applications presented in the Medical Devices Track: Strategies for Successful Implementation of mHealth in Low Resource Settings chaired by Walter Karlen, PhD, Grand Challenges Canada grantee and post-doc at University of British Columbia and Stellenbosch University.
Presented June 6, 2014, at UNESCO Technology for Development 2014, theme: What is Essential?, hosted by EPFL and CODEV in Lausanne, Switzerland. For more information: http://wiki.epfl.ch/opentech4dev
Please Message To Request Copy of this Presentation for Download
AI in Healthcare: From Hype to Impact (updated)Mei Chen, PhD
The primary goal of this workshop is to help health professionals gain a critical understanding of the various types of AI technologies available so they can make wise decisions and invest AI for healthcare improvement.
Bio IT World 2019 - AI For Healthcare - Simon Taylor, LucidworksLucidworks
Presentation from Bio IT World, Boston | April 16-18, 2019
Track: AI for Healthcare: Practical Application of AI in Clinical Healthcare
Session Title: To AI or Not to AI, That Is the Question
Speaker: Simon Taylor, Lucidworks
AI in Health Care: How to Implement Medical Imaging using Machine Learning?Skyl.ai
About the webinar
According to a report “The Digital Universe Driving Data Growth in Healthcare,” published by EMC with research and analysis from IDC, Hospitals are producing 50 petabytes of data per year. Almost 90% of this data is comprised of medical imaging i.e. digital images from scans like MRIs or CTs. More than 97% of this data goes unanalyzed or unused.
The top healthcare institutions across the globe are adopting AI in medical imaging to increase speed and imaging accuracy, monitor data in real-time and eliminate the need for humans to do time-consuming and complex tasks. This has been enabling doctors to optimize treatment approaches, speed of care and interconnected health conditions.
Through this webinar, we will understand how AI can be used to automate routine processes and procedures and help radiologists to identify patterns, and help in treating patients with critical conditions quickly.
What you'll learn
- How healthcare institutions are leveraging AI to augment decision making, prevent medical errors, and reduce costs in medical imaging
- Discuss the approach to automate machine learning workflow, creating and deploying models in hours, not weeks or months
- Demo: How to detect pneumonia from chest x-rays using AI within a few minutes using skyl.ai
To explore more, visit: https://skyl.ai/form?p=start-trial
Algorithms and bias: What lenders need to knowWhite & Case
The algorithms that power fintech may discriminate in ways that can be difficult to anticipate—and financial institutions can be held accountable even when alleged discrimination is clearly unintentional.
When it comes to AI use for prediction, diagnosis and treatment of medical conditions, reality is often replaced with a hype. Limitations should be known. A review of AI failures and challenges in healthcare showing why it is not likely for algorithms to replace physicians in the nearest future.
Healthcare AI will undoubtedly become one of the fastest growing industries in the industry. Although the medical and health artificial intelligence industry was valued at US$ 600 million in 2014 , it is expected to reach a staggering US$ 150 billion by 2026. There are countless AI applications in the healthcare industry, let’s look at some outstanding ones.
5 Powerful Real World Examples Of How AI Is Being Used In HealthcareBernard Marr
Healthcare can be transformed with the innovation and insights of artificial intelligence and machine learning. From robot-assisted surgery to virtual nursing assistants, diagnosing conditions, facilitating workflow and analyzing images, AI and machines can help improve outcomes for patients and lower costs for providers.
Gowlings - November 12, 2014
In an ever-increasing digital world, all businesses face challenges in managing and protecting sensitive and confidential information. In this presentation Gowlings and Marsh Canada Limited addressed best practices for responding to a cyber breach, and what types of insurance may be available to respond to such a loss. Topics included:
• Trends, and the evolution of cyber insurance/products
• The D&O connection, cyber is a strategic business risk
• Risk Management Strategies
• Best Practices in Breach Response.
The algorithms that are already changing your life By.Dr.Mahboob ali khan PhdHealthcare consultant
It is hoped that AI will relieve some of the pressure on busy hospitals by diagnosing disease and recommending treatment options quickly and efficiently.Medicine is primed to be a chief beneficiary of artificial intelligence. AI can diagnose diseases from telltale groups of symptoms, strange patterns in blood tests, and the subtle abnormalities that cells display as a disease begins takes hold. Time and again, AI systems are found to pick up signs of illness that are unknown to doctors, making the AIs more accurate as a result.
Artificial intelligence (AI) is already transforming healthcare. It's an invaluable tool, capable of storing and processing vast amounts of data almost simultaneously. AI allows for rapid and accurate diagnosis, early detection, advanced research and much more.
The Future of Artificial Intelligence and Quality Management in Hospitals By....Healthcare consultant
The medical device industry has noticed this factor and uses it to save lives. Artificial intelligence (AI) in the life sciences industry is capable of more than one could imagine and it’s changing the future. For example, one organization is creating AI-based voice robot technology, which, according to an article in Management Matters Network, will deliver custom prescriptive advice to managers using strengths and performance data to help better coach and engage employees.
Automated audit management has served as a great source of information to delve deeper into data with predictive intelligence regarding safety and compliance. Leading safety metrics provide:
• Total number of noncompliances
• Number of near-misses enabling investigation to prevent potential incidents
• The time it takes to complete post-audit corrective and preventive actions
• Easy-to-view previous findings for corrective action launches and findings
• Automated audit management software that centralizes all risk items and allows users to automatically assess them and generate reports quickly to pinpoint high-risk gaps that may otherwise go unnoticed
Healthcare delivery is becoming an increasingly complex operation. Nurses, physicians and other allied healthcare professionals are increasingly measured on their quality of work, even with increasing patient volume and patient complexity. Technology, from sensors to analytics to software based decision support and automation, have the potential to both leverage our healthcare provider workforce to mange increasing demands and to improve quality. This presentation will focus on the key areas of opportunity for technology to improve the capabilities of healthcare providers in delivering quality care.
Disruptors in the Medical Imaging IndustryBill Kelly
An overview of the Disruptors in the Medical Imaging Market. This free webinar will also give you more insight on the various factors that influence the market. We touch on results from a survey of a survey of 147 radiologists highlight the importance of reimbursement changes –both “appropriateness” measures and value-based medicine – as the most significant factors that will impact the imaging market.
The latest AI advances have the potential to massively improve our health and well being. In this talk, we will explore the most important opportunities for AI in healthcare. For example, we will explore how AI can diagnose major life-threatening conditions even before those conditions emerge. We will talk about AI's ability to recommend dramatically more effective and less harmful treatment plans based on AI's understanding of a patient's medical history and current conditions. Finally, we will talk about role of AI in making our healthcare system effective and affordable for everyone. In each part of this presentation, we will look at specific examples of how AI is used to address the COVID-19 pandemic.
Artificial Intelligence in Medical Imaging: An Analysis of Funding for Start-upsSimon Harris
There are over 50 start-up companies developing artificial intelligence solutions for medical imaging. Combined, these companies have raised over $100 million in funding. This short report from Signify Research shows the trends in capital funding for these companies and highlights how funding breaks down by company, by region and by clinical application.
"Challenges for AI in Healthcare" - Peter Graven Ph.DGrid Dynamics
Dynamic Talks Portland: The use of AI in many industries has revolutionized operations and efficiency. In healthcare, the progress is just beginning. Despite the promise of AI, why has the development lagged other industries? What issues are unique to healthcare that create challenges for common approaches? How can data scientists overcome these challenges and deliver on the promise of using data to reach multiple goals of improved quality, decreased cost, and greater patient satisfaction?
A Cognitive-Based Semantic Approach to Deep Content Analysis in Search EnginesMei Chen, PhD
We present a cognitive-based semantic approach that uses rule-based Natural Language Processing (NLP) in conjunction with a world model and cognitive frames to semantically analyze, understand, and rank digital text in search engines. The goal is to improve the relevance, accuracy, and efficiency of information search. The world model represents things existing in the real world (e.g., subject-related ontologies or classifications essential for understanding the topics to be analyzed) whereas cognitive frames specify possible users’ interactions with the world, including things that people should know or do (e.g., tasks, methods, procedures, cognitive processes) in such interactions. Using a rule-based semantic approach in conjunction with a subject-related world model and task-relevant cognitive frames to understand and evaluate text is innovative approach in search engine technology. It addresses three limitations of the existing approaches: the inadequate measure of the meaningful content in web pages; a poor understanding of users’ intention and tasks in their search and, the irrelevance and inaccuracy of search results. This method has led to the successful implementation of a full-scale semantic search engine in medicine (available at Seenso.com). The method is applicable and adaptable to other disciplines and other types of computer applications.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/02/opportunities-for-vision-in-healthcare-a-presentation-from-woodside-capital/
Vini Jolly, Executive Director at Woodside Capital, presents the “Vision Opportunities in Healthcare” tutorial at the September 2020 Embedded Vision Summit.
With advances in computer vision, AI/ML and data analytics, the pace of technological change continues to accelerate. Nowhere has the confluence of those technologies been more impactful than in Digital Health. Healthcare is an almost $4 trillion industry and continues to grow every year. But by some estimates about 25% of the overall healthcare spend ($1T!) is wasted.
This presentation not only examines the investment trends in digital health, but also dives into the specific verticals and domains where startups are leveraging computer vision and AI to disrupt healthcare by addressing efficiency, efficacy and hopefully affordability.
Artificial Intelligence Service in HealthcareAnkit Jain
It is no secret that artificial intelligence is shaping new business landscapes in every industries. As one of emerging convergence technologies, Artificial Intelligence (AI) creates new products and services, finally innovating business models. Especially, it has been noted by industry experts and researchers that healthcare sector has the biggest potential of AI convergence. In fact, major technology companies including Google, Microsoft and IBM have invested in AI in healthcare sector. Thousands of AI startups are active launching innovative services related to healthcare.
When it comes to AI use for prediction, diagnosis and treatment of medical conditions, reality is often replaced with a hype. Limitations should be known. A review of AI failures and challenges in healthcare showing why it is not likely for algorithms to replace physicians in the nearest future.
Healthcare AI will undoubtedly become one of the fastest growing industries in the industry. Although the medical and health artificial intelligence industry was valued at US$ 600 million in 2014 , it is expected to reach a staggering US$ 150 billion by 2026. There are countless AI applications in the healthcare industry, let’s look at some outstanding ones.
5 Powerful Real World Examples Of How AI Is Being Used In HealthcareBernard Marr
Healthcare can be transformed with the innovation and insights of artificial intelligence and machine learning. From robot-assisted surgery to virtual nursing assistants, diagnosing conditions, facilitating workflow and analyzing images, AI and machines can help improve outcomes for patients and lower costs for providers.
Gowlings - November 12, 2014
In an ever-increasing digital world, all businesses face challenges in managing and protecting sensitive and confidential information. In this presentation Gowlings and Marsh Canada Limited addressed best practices for responding to a cyber breach, and what types of insurance may be available to respond to such a loss. Topics included:
• Trends, and the evolution of cyber insurance/products
• The D&O connection, cyber is a strategic business risk
• Risk Management Strategies
• Best Practices in Breach Response.
The algorithms that are already changing your life By.Dr.Mahboob ali khan PhdHealthcare consultant
It is hoped that AI will relieve some of the pressure on busy hospitals by diagnosing disease and recommending treatment options quickly and efficiently.Medicine is primed to be a chief beneficiary of artificial intelligence. AI can diagnose diseases from telltale groups of symptoms, strange patterns in blood tests, and the subtle abnormalities that cells display as a disease begins takes hold. Time and again, AI systems are found to pick up signs of illness that are unknown to doctors, making the AIs more accurate as a result.
Artificial intelligence (AI) is already transforming healthcare. It's an invaluable tool, capable of storing and processing vast amounts of data almost simultaneously. AI allows for rapid and accurate diagnosis, early detection, advanced research and much more.
The Future of Artificial Intelligence and Quality Management in Hospitals By....Healthcare consultant
The medical device industry has noticed this factor and uses it to save lives. Artificial intelligence (AI) in the life sciences industry is capable of more than one could imagine and it’s changing the future. For example, one organization is creating AI-based voice robot technology, which, according to an article in Management Matters Network, will deliver custom prescriptive advice to managers using strengths and performance data to help better coach and engage employees.
Automated audit management has served as a great source of information to delve deeper into data with predictive intelligence regarding safety and compliance. Leading safety metrics provide:
• Total number of noncompliances
• Number of near-misses enabling investigation to prevent potential incidents
• The time it takes to complete post-audit corrective and preventive actions
• Easy-to-view previous findings for corrective action launches and findings
• Automated audit management software that centralizes all risk items and allows users to automatically assess them and generate reports quickly to pinpoint high-risk gaps that may otherwise go unnoticed
Healthcare delivery is becoming an increasingly complex operation. Nurses, physicians and other allied healthcare professionals are increasingly measured on their quality of work, even with increasing patient volume and patient complexity. Technology, from sensors to analytics to software based decision support and automation, have the potential to both leverage our healthcare provider workforce to mange increasing demands and to improve quality. This presentation will focus on the key areas of opportunity for technology to improve the capabilities of healthcare providers in delivering quality care.
Disruptors in the Medical Imaging IndustryBill Kelly
An overview of the Disruptors in the Medical Imaging Market. This free webinar will also give you more insight on the various factors that influence the market. We touch on results from a survey of a survey of 147 radiologists highlight the importance of reimbursement changes –both “appropriateness” measures and value-based medicine – as the most significant factors that will impact the imaging market.
The latest AI advances have the potential to massively improve our health and well being. In this talk, we will explore the most important opportunities for AI in healthcare. For example, we will explore how AI can diagnose major life-threatening conditions even before those conditions emerge. We will talk about AI's ability to recommend dramatically more effective and less harmful treatment plans based on AI's understanding of a patient's medical history and current conditions. Finally, we will talk about role of AI in making our healthcare system effective and affordable for everyone. In each part of this presentation, we will look at specific examples of how AI is used to address the COVID-19 pandemic.
Artificial Intelligence in Medical Imaging: An Analysis of Funding for Start-upsSimon Harris
There are over 50 start-up companies developing artificial intelligence solutions for medical imaging. Combined, these companies have raised over $100 million in funding. This short report from Signify Research shows the trends in capital funding for these companies and highlights how funding breaks down by company, by region and by clinical application.
"Challenges for AI in Healthcare" - Peter Graven Ph.DGrid Dynamics
Dynamic Talks Portland: The use of AI in many industries has revolutionized operations and efficiency. In healthcare, the progress is just beginning. Despite the promise of AI, why has the development lagged other industries? What issues are unique to healthcare that create challenges for common approaches? How can data scientists overcome these challenges and deliver on the promise of using data to reach multiple goals of improved quality, decreased cost, and greater patient satisfaction?
A Cognitive-Based Semantic Approach to Deep Content Analysis in Search EnginesMei Chen, PhD
We present a cognitive-based semantic approach that uses rule-based Natural Language Processing (NLP) in conjunction with a world model and cognitive frames to semantically analyze, understand, and rank digital text in search engines. The goal is to improve the relevance, accuracy, and efficiency of information search. The world model represents things existing in the real world (e.g., subject-related ontologies or classifications essential for understanding the topics to be analyzed) whereas cognitive frames specify possible users’ interactions with the world, including things that people should know or do (e.g., tasks, methods, procedures, cognitive processes) in such interactions. Using a rule-based semantic approach in conjunction with a subject-related world model and task-relevant cognitive frames to understand and evaluate text is innovative approach in search engine technology. It addresses three limitations of the existing approaches: the inadequate measure of the meaningful content in web pages; a poor understanding of users’ intention and tasks in their search and, the irrelevance and inaccuracy of search results. This method has led to the successful implementation of a full-scale semantic search engine in medicine (available at Seenso.com). The method is applicable and adaptable to other disciplines and other types of computer applications.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2021/02/opportunities-for-vision-in-healthcare-a-presentation-from-woodside-capital/
Vini Jolly, Executive Director at Woodside Capital, presents the “Vision Opportunities in Healthcare” tutorial at the September 2020 Embedded Vision Summit.
With advances in computer vision, AI/ML and data analytics, the pace of technological change continues to accelerate. Nowhere has the confluence of those technologies been more impactful than in Digital Health. Healthcare is an almost $4 trillion industry and continues to grow every year. But by some estimates about 25% of the overall healthcare spend ($1T!) is wasted.
This presentation not only examines the investment trends in digital health, but also dives into the specific verticals and domains where startups are leveraging computer vision and AI to disrupt healthcare by addressing efficiency, efficacy and hopefully affordability.
Artificial Intelligence Service in HealthcareAnkit Jain
It is no secret that artificial intelligence is shaping new business landscapes in every industries. As one of emerging convergence technologies, Artificial Intelligence (AI) creates new products and services, finally innovating business models. Especially, it has been noted by industry experts and researchers that healthcare sector has the biggest potential of AI convergence. In fact, major technology companies including Google, Microsoft and IBM have invested in AI in healthcare sector. Thousands of AI startups are active launching innovative services related to healthcare.
Producing Better and Affordable Healthcare Services Using Computational Intel...EMMAIntl
Computational Intelligence (CI) is one of the major pillars of Artificial Intelligence. It is the study, design, and development of intelligent software based on the theory of evolution. Within the past decade, healthcare has become expensive. Also, with the declining doctor-patient ratio, there are constant needs for computing systems for everything from executing simple tasks, such as booking appointments, to major services such as consulting and diagnosis...
April 2013 StartUp Health Insights Funding ReportStartUp Health
See StartUp Health Insights (http://www.startuphealth.com/insights) for the most comprehensive digital health funding database. Apply to StartUp Health Academy here: http://www.startuphealth.com/about-us/application/
We are pleased to present our review of the life sciences software market for the first half of 2019.
Madison Park Group is a unique investment banking firm that takes a "strategy first" approach to advising software companies. Our partners have developed and advised numerous successful companies as operators, investors and investment bankers.
Rohan Khanna and Jonathan Adler spearhead the firm's efforts in the space.
Generative AI in Healthcare Market - Copy - Copy.pptxGayatriGadhave1
Generative AI holds significant promise in healthcare, there are also challenges related to data privacy, model interpretability, and regulatory compliance that need to be addressed. Ethical considerations and thorough validation processes are crucial to ensure the responsible and safe application of generative AI techniques in healthcare.
The use of artificial intelligence in healthcare has the potential to assist healthcare providers in many aspects of patient care and administrative processes as well as improve patient outcomes.
AI analyzes data throughout a healthcare system to mine, automate and predict processes. Some of the use cases are :
1. Early Diagnosis of diseases
2. Improved clinical trial processes
3. Mental health apps etc.
Top 10 Mobile Healthcare App Development Trends 2022.pdfGroovy Web
With the support of technology and advancement, the healthcare industry is also growing rapidly just like other industries. The arrival of appearing app trends
Artificial intelligence enters the medical fieldRuchi Jain
In the medical and health field, artificial intelligence can help reduce the cost of ongoing health operations, and can have an impact on the quality of medical care for patients everywhere. By diagnosing diseases earlier, AI can also improve patient outcomes. No matter how you look at it, artificial intelligence has great potential in healthcare.
Medical Imaging: 8 Opportunities for technology entrepreneurs and investorsHealthstartup
There is tremendous opportunity currently to conduct advanced analysis of imaging data for diagnostic and treatment planning purposes, to combine imaging data from various sources and to share images for better medical collaboration. While medical imaging used to be the exclusive domain of large multinational medical devices companies, startups are entering the fray with software-based solutions and clever use of open-source or consumer-based technologies.
mHealth Israel_Anne LeGrand_IBM Watson_Big Data in HealthcareLevi Shapiro
Presentation by Anne LeGrand, VP Imaging, IBM Watson HEALTH: Big Data in Healthcare. Includes a future with AI; Industry Challenges; Natural Language Processing; Deep Learning; Make the Invisible, Visible; Accelerating the Pace of Drug Discovery; Become a Trusted Advisor; Treatment Recommendations by Cognitive Computing; Derive Actionable Insights; Managing Care and Improving Lives; Identifying Outcomes of Precision Cohorts; Diabetes; Medical Imaging; Market Size; AI Value; Imaging AI Market; How to Set Priorities; Safety Net; Global Issues; Watson Health Imaging Strategy; Maturity Curve; Precision Medicine; Watson Imaging Clinical Review; Key Principles;
The 10 most innovative medical devices companies 2018insightscare
Despite these challenges, medical device companies have always been adept with the latest technology and innovations happening in the sector. Keeping this in mind, we bring you the in-depth profiles of- “The 10 Most Innovative Medical Devices Companies 2018.”
Artificial Intelligence in Healthcare.pdfayushiqss
Imagine a parallel world, where everyone could know about their future health and any diseases they might have in later years. Now, come back to the real world where you no longer need to imagine anything. Everything is possible now with the integration of Artificial Intelligence in healthcare. Humans are developing the best AI and ML-powered devices that can predict your future health.
The Pros & Cons of Brexit for UK’s Automotive & Healthcare IndustriesRNayak3
Learn about the implications of Brexit on the automotive and healthcare industries in the U.K. The Pros & Cons of Brexit for UK’s Automotive & Healthcare Industries. Learn more: https://www.wns.com/perspectives/blogs/blogdetail/781/the-pros-and-cons-of-brexit-for-uks-automotive-and-healthcare-industries
Similar to "Vision Opportunities in Healthcare," a Presentation from Woodside Capital Partners (20)
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/opencv-for-high-performance-low-power-vision-applications-on-snapdragon-a-presentation-from-qualcomm/
Xin Zhong, Computer Vision Product Manager at Qualcomm Technologies, presents the “OpenCV for High-performance, Low-power Vision Applications on Snapdragon” tutorial at the May 2024 Embedded Vision Summit.
For decades, the OpenCV software library has been popular for developing computer vision applications. However, developers have found it challenging to create efficient implementations of their OpenCV applications on processors optimized for edge applications, like the Qualcomm Snapdragon family. As part of its comprehensive support for computer vision application developers, Qualcomm provides a variety of tools to enable developers to take full advantage of the heterogeneous computing resources in the Snapdragon processors.
In this talk, Zhong introduces a new element of Qualcomm’s computer vision tools suite: a version of OpenCV optimized for Snapdragon platforms, which allows developers to leverage and port their existing OpenCV-based applications seamlessly to Snapdragon platforms. Supporting OpenCV v4.x and later releases, this implementation contains unique Qualcomm-specific accelerations of OpenCV and OpenCV extension APIs. Zhong explains how this library enables developers to leverage existing OpenCV code to achieve superior performance and power savings on Snapdragon platforms.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/deploying-large-models-on-the-edge-success-stories-and-challenges-a-presentation-from-qualcomm/
Vinesh Sukumar, Senior Director of Product Management at Qualcomm Technologies, presents the “Deploying Large Models on the Edge: Success Stories and Challenges” tutorial at the May 2024 Embedded Vision Summit.
In this talk, Dr. Sukumar explains and demonstrates how Qualcomm has been successful in deploying large generative AI and multimodal models on the edge for a variety of use cases in consumer and enterprise markets. He examines key challenges that must be overcome before large models at the edge can reach their full commercial potential. He also highlights how Qualcomm is addressing these challenges through upgraded processor hardware, improved developer tools and a comprehensive library of fully optimized AI models in the Qualcomm AI Hub.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/scaling-vision-based-edge-ai-solutions-from-prototype-to-global-deployment-a-presentation-from-network-optix/
Maurits Kaptein, Chief Data Scientist at Network Optix and Professor at the University of Eindhoven, presents the “Scaling Vision-based Edge AI Solutions: From Prototype to Global Deployment” tutorial at the May 2024 Embedded Vision Summit.
The Embedded Vision Summit brings together innovators in silicon, devices, software and applications and empowers them to bring computer vision and perceptual AI into reliable and scalable products. However, integrating recent hardware, software and algorithm innovations into prime-time-ready products is quite challenging. Scaling from a proof of concept—for example, a novel neural network architecture performing a valuable task efficiently on a new piece of silicon—to an AI vision system installed in hundreds of sites requires surmounting myriad hurdles.
First, building on Network Optix’s 14 years of experience, Professor Kaptein details how to overcome the networking, fleet management, visualization and monetization challenges that come with scaling a global vision solution. Second, Kaptein discusses the complexities of making vision AI solutions device-agnostic and remotely manageable, proposing an open standard for AI model deployment to edge devices. The proposed standard aims to simplify market entry for silicon manufacturers and enhance scalability for solution developers. Kaptein outlines the standard’s core components and invites collaborative contributions to drive market expansion.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/whats-next-in-on-device-generative-ai-a-presentation-from-qualcomm/
Jilei Hou, Vice President of Engineering and Head of AI Research at Qualcomm Technologies, presents the “What’s Next in On-device Generative AI” tutorial at the May 2024 Embedded Vision Summit.
The generative AI era has begun! Large multimodal models are bringing the power of language understanding to machine perception, and transformer models are expanding to allow machines to understand using multiple types of sensors. This new wave of approaches is poised to revolutionize user experiences, disrupt industries and enable powerful new capabilities. For generative AI to reach its full potential, however, we must deploy it on edge devices, providing improved latency, pervasive interaction and enhanced privacy.
In this talk, Hou shares Qualcomm’s vision of the compelling opportunities enabled by efficient generative AI at the edge. He also identifies the key challenges that the industry must overcome to realize the massive potential of these technologies. And he highlights research and product development work that Qualcomm is doing to lead the way via an end-to-end system approach—including techniques for efficient on-device execution of LLMs, LVMs and LMMs, methods for orchestration of large models at the edge and approaches for adaptation and personalization.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/learning-compact-dnn-models-for-embedded-vision-a-presentation-from-the-university-of-maryland-at-college-park/
Shuvra Bhattacharyya, Professor at the University of Maryland at College Park, presents the “Learning Compact DNN Models for Embedded Vision” tutorial at the May 2023 Embedded Vision Summit.
In this talk, Bhattacharyya explores methods to transform large deep neural network (DNN) models into effective compact models. The transformation process that he focuses on—from large to compact DNN form—is referred to as pruning. Pruning involves the removal of neurons or parameters from a neural network. When performed strategically, pruning can lead to significant reductions in computational complexity without significant degradation in accuracy. It is sometimes even possible to increase accuracy through pruning.
Pruning provides a general approach for facilitating real-time inference in resource-constrained embedded computer vision systems. Bhattacharyya provides an overview of important aspects to consider when applying or developing a DNN pruning method and presents details on a recently introduced pruning method called NeuroGRS. NeuroGRS considers structures and trained weights jointly throughout the pruning process and can result in significantly more compact models compared to other pruning methods.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/introduction-to-computer-vision-with-cnns-a-presentation-from-mohammad-haghighat/
Independent consultant Mohammad Haghighat presents the “Introduction to Computer Vision with Convolutional Neural Networks” tutorial at the May 2023 Embedded Vision Summit.
This presentation covers the basics of computer vision using convolutional neural networks. Haghighat begins by introducing some important conventional computer vision techniques and then transition to explaining the basics of machine learning and convolutional neural networks (CNNs) and showing how CNNs are used in visual perception.
Haghighat illustrates the building blocks and computational elements of neural networks through examples. This session provides an overview of how modern computer vision algorithms are designed, trained and used in real-world applications.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/selecting-tools-for-developing-monitoring-and-maintaining-ml-models-a-presentation-from-yummly/
Parshad Patel, Data Scientist at Yummly, presents the “Selecting Tools for Developing, Monitoring and Maintaining ML Models” tutorial at the May 2023 Embedded Vision Summit.
With the boom in tools for developing, monitoring and maintaining ML models, data science teams have many options to choose from. Proprietary tools provided by cloud service providers are enticing, but teams may fear being locked in—and may worry that these tools are too costly or missing important features when compared with alternatives from specialized providers.
Fortunately, most proprietary, fee-based tools have an open-source component that can be integrated into a home-grown solution at low cost. This can be a good starting point, enabling teams to get started with modern tools without making big investments and leaving the door open to evolve tool selection over time. In this talk, Patel presents a step-by-step process for creating an MLOps tool set that enables you to deliver maximum value as a data scientist. He shares how Yummly built pipelines for model development and put them into production using open-source projects.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/building-accelerated-gstreamer-applications-for-video-and-audio-ai-a-presentation-from-wave-spectrum/
Abdo Babukr, Accelerated Computing Consultant at Wave Spectrum, presents the “Building Accelerated GStreamer Applications for Video and Audio AI,” tutorial at the May 2023 Embedded Vision Summit.
GStreamer is a popular open-source framework for creating streaming media applications. Developers often use GStreamer to streamline the development of computer vision and audio perception applications. Since perceptual algorithms are often quite demanding in terms of processing performance, in many cases developers need to find ways to accelerate key GStreamer building blocks, taking advantage of specialized features of their target processor or co-processor.
In this talk, Babukr introduces GStreamer and shows how to use it to build computer vision and audio perception applications. He also shows how to create efficient, high-performance GStreamer applications that utilize specialized hardware features.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/understanding-selecting-and-optimizing-object-detectors-for-edge-applications-a-presentation-from-walmart-global-tech/
Md Nasir Uddin Laskar, Staff Machine Learning Engineer at Walmart Global Tech, presents the “Understanding, Selecting and Optimizing Object Detectors for Edge Applications” tutorial at the May 2023 Embedded Vision Summit.
Object detectors count objects in a scene and determine their precise locations, while also labeling them. Object detection plays a crucial role in many vision applications, from autonomous driving to smart appliances. In many of these applications, it’s necessary or desirable to implement object detection at the edge.
In this presentation, Laskar explores the evolution of object detection algorithms, from traditional approaches to deep learning-based methods and transformer-based architectures. He delves into widely used approaches for object detection, such as two-stage R-CNNs and one-stage YOLO algorithms, and examines their strengths and weaknesses. And he provides guidance on how to evaluate and select an object detector for an edge application.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/introduction-to-modern-lidar-for-machine-perception-a-presentation-from-the-university-of-ottawa/
Robert Laganière, Professor at the University of Ottawa and CEO of Sensor Cortek, presents the “Introduction to Modern LiDAR for Machine Perception” tutorial at the May 2023 Embedded Vision Summit.
In this presentation, Laganière provides an introduction to light detection and ranging (LiDAR) technology. He explains how LiDAR sensors work and their main advantages and disadvantages. He also introduces different approaches to LiDAR, including scanning and flash LiDAR.
Laganière explores the types of data produced by LiDAR sensors and explains how this data can be processed using deep neural networks. He also examines the synergy between LiDAR and cameras, and the concept of pseudo-LiDAR for detection.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/11/vision-language-representations-for-robotics-a-presentation-from-the-university-of-pennsylvania/
Dinesh Jayaraman, Assistant Professor at the University of Pennsylvania, presents the “Vision-language Representations for Robotics” tutorial at the May 2023 Embedded Vision Summit.
In what format can an AI system best present what it “sees” in a visual scene to help robots accomplish tasks? This question has been a long-standing challenge for computer scientists and robotics engineers. In this presentation, Jayaraman provides insights into cutting-edge techniques being used to help robots better understand their surroundings, learn new skills with minimal guidance and become more capable of performing complex tasks.
Jayaraman discusses recent advances in unsupervised representation learning and explains how these approaches can be used to build visual representations that are appropriate for a controller that decides how the robot should act. In particular, he presents insights from his research group’s recent work on how to represent the constituent objects and entities in a visual scene, and how to combine vision and language in a way that permits effectively translating language-based task descriptions into images depicting the robot’s goals.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/adas-and-av-sensors-whats-winning-and-why-a-presentation-from-techinsights/
Ian Riches, Vice President of the Global Automotive Practice at TechInsights, presents the “ADAS and AV Sensors: What’s Winning and Why?” tutorial at the May 2023 Embedded Vision Summit.
It’s clear that the number of sensors per vehicle—and the sophistication of these sensors—is growing rapidly, largely thanks to increased adoption of advanced safety and driver assistance features. In this presentation, Riches explores likely future demand for automotive radars, cameras and LiDARs.
Riches examines which vehicle features will drive demand out to 2030, how vehicle architecture change is impacting the market and what sorts of compute platforms these sensors will be connected to. Finally, he shares his firm’s vision of what the landscape could look like far beyond 2030, considering scenarios out to 2050 for automated driving and the resulting sensor demand.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/computer-vision-in-sports-scalable-solutions-for-downmarkets-a-presentation-from-sportlogiq/
Mehrsan Javan, Co-founder and CTO of Sportlogiq, presents the “Computer Vision in Sports: Scalable Solutions for Downmarket Leagues” tutorial at the May 2023 Embedded Vision Summit.
Sports analytics is about observing, understanding and describing the game in an intelligent manner. In practice, this requires a fully automated, robust end-to-end pipeline, spanning from visual input, to player and group activities, to player and team evaluation to planning. Despite major advancements in computer vision and machine learning, today sports analytics solutions are limited to top leagues and are not widely available for downmarket leagues and youth sports.
In this talk, Javan explains how his company has developed scalable and robust computer vision solutions to democratize sport analytics and offer pro-league-level insights to leagues with modest resources, including youth leagues. He highlights key challenges—such as the requirement for low-cost, low-latency processing and the need for robustness despite variations in venues. He discusses the approaches Sportlogiq tried and how it ultimately overcame these challenges, including the use of transformers and fusion of multiple type of data streams to maximize accuracy.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/detecting-data-drift-in-image-classification-neural-networks-a-presentation-from-southern-illinois-university/
Spyros Tragoudas, Professor and School Director at Southern Illinois University Carbondale, presents the “Detecting Data Drift in Image Classification Neural Networks” tutorial at the May 2023 Embedded Vision Summit.
An unforeseen change in the input data is called “drift,” and may impact the accuracy of machine learning models. In this talk, Tragoudas presents a novel scheme for diagnosing data drift in the input streams of image classification neural networks. His proposed method for drift detection and quantification uses a threshold dictionary for the prediction probabilities of each class in the neural network model.
The method is applicable to any drift type in images such as noise and weather effects, among others. Tragoudas shares experimental results on various data sets, drift types and neural network models to show that his proposed method estimates the drift magnitude with high accuracy, especially when the level of drift significantly impacts the model’s performance.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/deep-neural-network-training-diagnosing-problems-and-implementing-solutions-a-presentation-from-sensor-cortek/
Fahed Hassanat, Chief Operating Officer and Head of Engineering at Sensor Cortek, presents the “Deep Neural Network Training: Diagnosing Problems and Implementing Solutions” tutorial at the May 2023 Embedded Vision Summit.
In this presentation, Hassanat delves into some of the most common problems that arise when training deep neural networks. He provides a brief overview of essential training metrics, including accuracy, precision, false positives, false negatives and F1 score.
Hassanat then explores training challenges that arise from problems with hyperparameters, inappropriately sized models, inadequate models, poor-quality datasets, imbalances within training datasets and mismatches between training and testing datasets. To help detect and diagnose training problems, he also covers techniques such as understanding performance curves, recognizing overfitting and underfitting, analyzing confusion matrices and identifying class interaction issues.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/ai-start-ups-the-perils-of-fishing-for-whales-war-stories-from-the-entrepreneurial-front-lines-a-presentation-from-seechange-technologies/
Tim Hartley, Vice President of Product for SeeChange Technologies, presents the “AI Start-ups: The Perils of Fishing for Whales (War Stories from the Entrepreneurial Front Lines)” tutorial at the May 2023 Embedded Vision Summit.
You have a killer idea that will change the world. You’ve thought through product-market fit and differentiation. You have seed funding and a world-beating team. Best of all, you’ve caught the attention of major players in your industry. You’ve reached peak “start-up”—that point of limitless possibility—when you go to bed with the same level of energy and enthusiasm you had when you woke. And then the first proof of concept starts…
In this talk, Hartley lays out some of the pitfalls that await those building the next big thing. Using real examples, he shares some of the dos and don’ts, particularly when dealing with that big potential first customer. Hartley discusses the importance of end-to-end design, ensuring your product solves real-world problems. He explores how far the big companies will tell you to jump—and then jump again—for free. And, most importantly, how to build long-term partnerships with major corporations without relying on over-promising sales pitches.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/a-computer-vision-system-for-autonomous-satellite-maneuvering-a-presentation-from-scout-space/
Andrew Harris, Spacecraft Systems Engineer at SCOUT Space, presents the “Developing a Computer Vision System for Autonomous Satellite Maneuvering” tutorial at the May 2023 Embedded Vision Summit.
Computer vision systems for mobile autonomous machines experience a wide variety of real-world conditions and inputs that can be challenging to capture accurately in training datasets. Few autonomous systems experience more challenging conditions than those in orbit. In this talk, Harris describes how SCOUT Space has designed and trained satellite vision systems using dynamic and physically informed synthetic image datasets.
Harris describes how his company generates synthetic data for this challenging environment and how it leverages new real-world data to improve our datasets. In particular, he explains how these synthetic datasets account for and can replicate real sources of noise and error in the orbital environment, and how his company supplements them with in-space data from the first SCOUT-Vision system, which has been in orbit since 2021.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/bias-in-computer-vision-its-bigger-than-facial-recognition-a-presentation-from-santa-clara-university/
Susan Kennedy, Assistant Professor of Philosophy at Santa Clara University, presents the “Bias in Computer Vision—It’s Bigger Than Facial Recognition!” tutorial at the May 2023 Embedded Vision Summit.
As AI is increasingly integrated into various industries, concerns about its potential to reproduce or exacerbate bias have become widespread. While the use of AI holds the promise of reducing bias, it can also have unintended consequences, particularly in high-stakes computer vision applications such as facial recognition. However, even seemingly low-stakes computer vision applications such as identifying potholes and damaged roads can also present ethical challenges related to bias.
This talk explores how bias in computer vision often poses an ethical challenge, regardless of the stakes involved. Kennedy discusses the limitations of technical solutions aimed at mitigating bias, and why “bias-free” AI may not be achievable. Instead, she focuses on the importance of adopting a “bias-aware” approach to responsible AI design and explores strategies that can be employed to achieve this.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/sensor-fusion-techniques-for-accurate-perception-of-objects-in-the-environment-a-presentation-from-sanborn-map-company/
Baharak Soltanian, Vice President of Research and Development for the Sanborn Map Company, presents the “Sensor Fusion Techniques for Accurate Perception of Objects in the Environment” tutorial at the May 2023 Embedded Vision Summit.
Increasingly, perceptual AI is being used to enable devices and systems to obtain accurate estimates of object locations, speeds and trajectories. In demanding applications, this is often best done using a heterogeneous combination of sensors (e.g., vision, radar, LiDAR). In this talk, Soltanian introduces techniques for combining data from multiple sensors to obtain accurate information about objects in the environment.
Soltanian briefly introduces the roles played by Kalman filters, particle filters, Bayesian networks and neural networks in this type of fusion. She then examines alternative fusion architectures, such as centralized and decentralized approaches, to better understand the trade-offs associated with different approaches to sensor fusion as used to enhance the ability of machines to understand their environment.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
2. 2
Introduction to WCP
AutoTech Report
▪ M&A, strategic partnerships, and corporate finance advisory
▪ Focused on emerging growth technology companies
▪ Founded in 2001: over $8 billion in transaction value
▪ Offices in Silicon Valley, London, Shanghai
▪ Dedicated Digital Health and Computer Vision corporate
finance practice
Digital Health Artificial Intelligence
Collaborative Robots
3. Embedded Vision / Visual AI Market Map
Camera
Modules
Sensors Illumination Lenses
Cameras Processors
Boards and
Modules
Processors
and SoCs
SoftwareMemory
Enabling
Services & Tools
Development
Tools
Image & Video
Data
Standards
Components
Subsystems
Open SourceDesign &
Manufacturing
Services
Silicon IP
Automotive
Tier 1
Suppliers
Consumer
RetailTransportation
Industrial Security &
Surveillance
Defense &
Aerospace
Communication Media &
Entertainment
Agriculture
Healthcare
EnablingTechnologiesSystems&Solutions
3
4. Market Size – US Health Spending
United States, 1967 to 2017, Selected Years, and 10-year Projection
4
$52 $174
$517
$1,135
$2,295
$3,492
$5,963
$0
$1,000
$2,000
$3,000
$4,000
$5,000
$6,000
$7,000
1967 1977 1987 1997 2007 2017 2027P
Billions
Source: CMS.gov
6. US Healthcare Spending by Type of Product/Service
33%
20%9%
5%
5%
4%
3%
3%
2%
2%
14%
Hospital Care
Physician and Clinical Services
Retail Prescription Drugs
Other Health, Residential and Personal
Care Services
Nursing Care Facilities and Continuing
Care Retirement Communities
Dental Services
Home Health Care
Other Professional Services
Other Non-Durable Medical Products
Durable Medical Equipment
OthersTotal Spending: USD3.65 tn
6Source: CMS.gov
7. US Healthcare Spending – Key Facts
Total spending on
healthcare by
Americans in 2018
USD3.65 tn
Growth in spending
over 2017
4.4%
Estimated growth in
spending during
2018 - 2027
5.5%
Spending per person
USD11,212
Spending goes to
hospitals, doctors,
and clinical services
GDP share related to
healthcare spending
17.7%59%
Of all medical
spending goes to
waste
25%
Number of deaths
due to misdiagnosis
40,000 – 80,000
7Source: CMS.gov
8. Benefits of Computer Vision in Healthcare
• More accurate diagnoses of
medical image data
• Reduce redundant surgical
procedures and expensive
therapies
• Detect the slightest presence of a
condition
Precise Diagnoses
• Many fatal illnesses need to be
diagnosed in their early stages.
CV enables the early detection
of symptoms leading to timely
treatment and increased
probability of survival
Timely Detection of
Illness
• The use of CV in healthcare can
lessen the time doctors take in
analyzing reports and images – thus
giving them more time to spend
with patients and provide
personalized and constructive
advice
Improved Patient
Care
• CV technology enables doctors to
remotely monitor and analyze
health and fitness metrics to
assist patients to make faster and
better medical decisions
Health
Monitoring
• CV enables
pharmaceutical
companies to
significantly increase
throughput
Reduce Drug
Development Costs
8
13. Bringing AI and Deep Learning to pathology to automate rapid and accurate diagnoses
AI for radiology (CT and X-ray) to detect abnormalities and speed time to diagnoses for
everything from bone density to cranial bleeding
AI and Cloud Supercomputing for fast, accurate image analysis especially for
cardiovascular and lung conditions
Brings affordable, scalable and accurate blood diagnostics to the point-of-care, thereby
accelerating better patient outcomes and improving healthcare for all
Visualization & Deep Learning for drug discovery
Securely stream patient photographs and wound analysis directly to your desktop
Designer of a medical imaging device that reduces the cost of real-time and 3D imaging
and treatment
Non-invasive coronary artery disease detection using 3D image rendering
Machine vision based facial analysis to identify patient adherence
Machine vision to analyze movement and falls for patients/seniors
Using computer vision for remote health monitoring
Cutting Edge Computer Vision Healthcare Companies
13Source: Crunchbase
14. 14
Centralized vs. Remote Data Acquisition
Source: Company Websites, Secondary Research
Lab Diagnostic Cardiology DNA Testing MRI CT ScanUltrasound
Centralized Data Acquisition & Analytics
Opthalmology DermatologyCrib Cam Lab Diagnostics
Remote
Monitoring Bio-monitoring
Point of Care/Remote Data Acquisition & Analytics
15. Best Funded Companies in Computer Vision Healthcare
Company Name Deal Date
Company
Stage
Overview
Recent
Funding ($M)
Pre-money
Valuation ($M)
Tempus, United States 5/30/2019 Series F Developer of a health care data analytics platform designed to improve patient
outcomes.
$200.00 $3,100.00
PathAI, United States 4/17/2019 Series B Developer of an AI-powered research platform intended to improve the accuracy and
efficiency of cancer diagnosis and treatment.
$60.00
-
Healthy.io, Israel 9/11/2019 Series C The company's computer vision and artificial intelligence algorithms based platform
captures test strip images using smartphone camera, analyze chemical color of urine
test strips and give instant reports.
$60.00
-
ImagenTechnologies,
United States
9/12/2018 Series B Developer of a medical diagnostic technology designed to offer medical imaging services
to reduce diagnostic errors and improve patient outcomes.
$41.00 $75.00
Paige.ai, United States 11/27/2019 Series B Developer of computational pathology modules intended for rapid diagnostic
stratification, cancer detection, tumor segmentation, prediction of treatment response
and overall survival.
$33.69 $208.69
Arterys, United States 11/3/2017 Series B Developer of a medical imaging analytics platform designed to offer improved patient
care.
$30.60 $52.00
OrCam, Israel 2/20/2018 Provider of a portable artificial vision device designed to help the visually impaired
understand text and identify objects easily.
$30.40 $1,000.00
Sight Diagnostics, Israel 2/14/2019 Series B Developer of automated microscopy device designed to improve healthcare for
everyone through smarter blood testing.
$27.80
-
AiCure, United States 11/7/2019 Series C Provider of an intelligent medical assistant services designed to leverage a visual
recognition platform to monitor patient progress.
$24.50
-
Gauss Surgical, United
States
10/17/2018 Series C The company leverages computer vision and machine learning to deliver mobile
applications for the operating room, with a focus on improving patient safety, quality
and outcomes.
$20.00 $75.00
15
17. Big Tech Transforming Healthcare (1/2)
Large data companies like Google, Amazon and Apple are making huge strides into healthcare as
technological advancements have enabled digital healthcare to advance rapidly
• Most active big tech firm in
healthcare AI initiatives
• Founded Verily in 2015
• Project Medical Digital Assist
focused on AI usage in
physician assistance
• Developed algorithm to
diagnose diabetic
retinopathy in images
• Acquired fitness activity
tracker Fitbit for $2.1 billion
• Partnered with biotech firms
C4 Therapeutics and AbbVie
pharmaceuticals via Calico
• Corporate healthcare system
– Amazon Care
• Purchased online pharmacy
startup PillPack
• Plans to sell medical records
reading software
• Working on cancer research
and other healthcare related
ventures such as last-mile
delivery
• Focus on patient facing
products as well as
streamlining medical
payments
• Received FDA clearance for
new heart monitoring Apple
Watch feature (EKG)
• Implementing Apple Health
Records system through
hospital partnerships
• Acquired sleep monitor
company Beddit (May 2017)
and personal health data
platform Gliimpse (2016)
17
18. Big Tech Transforming Healthcare (2/2)
The healthcare industry presents tremendous business opportunity, encouraging other top tech
companies to adopt healthcare innovation
• Launched health care division
in 2017 that focuses on AI for
patient care improvement
• Alliance with Walgreens to
develop new health care
innovations
• Offering healthcare focused
solutions through Azure suite
• Collaborative research on
applying AI to MRI scans
• Acquires neural interface
startup CTRL-Labs for its mind-
reading wristband
• Plans to launch “Preventive
Health” tool to prompt users
to get regular checkups
• Acquired predictive healthcare
technology business of
BioSensics
• Bought seniors-focused health
services company Critical
Signal Technologies and
GreatCall, emergency
concierge & monitoring
services provider
• Acquired Auris Health’s robotic
platform technology used in
diagnostic and lung therapeutic
procedures
• Partnered with accelerator
Founders Factory with focus on
startups in the consumer
healthcare space
• Intel Capital invested in
Lumiata, which improves
quality of hospital care through
data and predictive analytics
• Invested in EchoPixel, which is
developing tools to enable
non-invasive colon cancer
screening
• Launched Uber Health: non-
medical-emergency
transportation service
18
19. FDA Gears for Innovation in Medical Technology
As shift towards new technologies gains momentum, the FDA has worked to modernize their
regulatory approach to facilitate innovation to improve the healthcare system:
Proposed regulatory
framework for dynamic AI
systems to ensure realization
of the full potential of the
technology
Approval of 106 novel
devices in 2018, including
artificial intelligence based
technologies for diabetic
retinopathy diagnosis
Creation of a Center for
Excellence for Digital Health
to complement the advances
in software-based devices
Digital Health Innovation Action Plan 2017
• Regulatory exclusion of certain medical software and lifestyle mobile apps under the
revised 21st Century Cures Act
• Development of a precertification program for faster launches for certain products
(including AI based products)
• Growing FDA’s medical software technology expertise through talent hiring
19
20. Future Trends
Key Trends
5G will enable distributed computing and push
the real-time analytics envelope
FDA will continue to embrace Software as a
Medical Device (SaMD) to approve diagnoses of
an increasingly broader swath of conditions
Combination of AI/ML/DL + high resolution
imaging/capture will continue to democratize
CV, especially in areas like lab diagnostics
Precision medicine is becoming reality: closed
loop from drug discovery to therapy,
adherence/compliance/and impact
Oncology/Radiology/Pathology will become
increasingly automated as AI/DL algorithms
continue to improve
Portable devices as well as smart phones or
smart phone-based peripherals will continue to
“consumerize” healthcare
20
21. Important Disclosure
21
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