The Singularity Pyramid (SP) is a 3D model that maps all kinds of knowledge in relation to each other across two dimensions: from technical to insightful, and from resource-constrained to resource-unconstrained. In the third dimension, knowledge is connected to smaller objects like data and information, or combined into larger objects like disciplines, technologies, and problems. The SP will help crowdsource widely recognized insights, analyze relationships between problems and solutions, compare levels of understanding between individuals and fields, and serve as a precursor to a superintelligence's brain. The creator plans to build out the SP by gathering a team with expertise in various fields to detail the data structure and map relationships within their projects and across disciplines.
Era of Artificial Intelligence Lecture 3 Pietro LeoPietro Leo
This document summarizes a lecture by Pietro Leo on artificial intelligence. Some key points discussed include:
- AI can help industries like agriculture, automotive, and healthcare. For agriculture, precision agriculture using AI is discussed.
- For science, big data acts as a microscope for the 21st century, enabling analysis like wine DNA tracing. Mapping the microbiome can also help protect from harmful bacteria.
- Digital twins of farms can help share insights and data to help farming. AI sensors may also detect foodborne pathogens at home.
- In automotive, self-driving vehicles are discussed as well as predictive maintenance using cloud, AI and connected cars. Damage assessment systems can also help standardize
The document discusses the rise of big data and how organizations can leverage it. It defines big data as data that cannot be analyzed with traditional tools due to its large volume, velocity, and variety. It describes how technological advances have led to more data being generated and collected from a variety of sources. The document advocates that organizations must find ways to analyze all this data to gain valuable insights that can improve decision making, customer experiences, and business strategies. It provides several examples of how companies in different industries have successfully used big data analytics.
Big Data has recently gained relevance because companies are realizing what it can do for them and that it is a gold mine for finding competitive advantages. Proximity’s Juan Manuel Ramírez, Director of Strategy and...
The document discusses how big data is enabling new opportunities for companies to better understand customer behavior and make more informed decisions. It defines big data as information that cannot be analyzed with traditional tools due to its large volume, velocity, and variety. Examples are provided of how companies in various industries like retail, healthcare, and transportation are using big data analytics to improve operations, prevent fraud, and personalize customer experiences. The importance of accessibility and technologies like Hadoop for making big data solutions more widely available is also covered.
Trendcasting for 2019 - What Will the Tuture of Tech HoldBrian Pichman
Join Brian Pichman of the Evolve Project as he highlights this year’s most significant technology trends and what it means for 2019. What changes are on the horizon? What technologies falling to the wayside? What technologies are on the verge of significant changes? What technologies should we expect to see flourish in the upcoming year?
The document discusses the initiation and integration of artificial intelligence in medical schools and colleges. It provides an overview of how medicine is changing with advancements in AI and machine learning, which are reshaping how doctors practice. It also examines the role of AI in medical education, with many seeing it as an assistive tool that can improve access to information for physicians and help make more accurate diagnoses. Concerns about reduced need for doctors and unemployment for students are mentioned but most see AI as a partner rather than a replacement for human physicians.
Potential use cases for use of Big Data in Pharma R&D. Also trying to take some of the hype out of the topic and present some tools that can be used to link and analyse data eventhough they are not really Big data (just important data)
The Singularity Pyramid (SP) is a 3D model that maps all kinds of knowledge in relation to each other across two dimensions: from technical to insightful, and from resource-constrained to resource-unconstrained. In the third dimension, knowledge is connected to smaller objects like data and information, or combined into larger objects like disciplines, technologies, and problems. The SP will help crowdsource widely recognized insights, analyze relationships between problems and solutions, compare levels of understanding between individuals and fields, and serve as a precursor to a superintelligence's brain. The creator plans to build out the SP by gathering a team with expertise in various fields to detail the data structure and map relationships within their projects and across disciplines.
Era of Artificial Intelligence Lecture 3 Pietro LeoPietro Leo
This document summarizes a lecture by Pietro Leo on artificial intelligence. Some key points discussed include:
- AI can help industries like agriculture, automotive, and healthcare. For agriculture, precision agriculture using AI is discussed.
- For science, big data acts as a microscope for the 21st century, enabling analysis like wine DNA tracing. Mapping the microbiome can also help protect from harmful bacteria.
- Digital twins of farms can help share insights and data to help farming. AI sensors may also detect foodborne pathogens at home.
- In automotive, self-driving vehicles are discussed as well as predictive maintenance using cloud, AI and connected cars. Damage assessment systems can also help standardize
The document discusses the rise of big data and how organizations can leverage it. It defines big data as data that cannot be analyzed with traditional tools due to its large volume, velocity, and variety. It describes how technological advances have led to more data being generated and collected from a variety of sources. The document advocates that organizations must find ways to analyze all this data to gain valuable insights that can improve decision making, customer experiences, and business strategies. It provides several examples of how companies in different industries have successfully used big data analytics.
Big Data has recently gained relevance because companies are realizing what it can do for them and that it is a gold mine for finding competitive advantages. Proximity’s Juan Manuel Ramírez, Director of Strategy and...
The document discusses how big data is enabling new opportunities for companies to better understand customer behavior and make more informed decisions. It defines big data as information that cannot be analyzed with traditional tools due to its large volume, velocity, and variety. Examples are provided of how companies in various industries like retail, healthcare, and transportation are using big data analytics to improve operations, prevent fraud, and personalize customer experiences. The importance of accessibility and technologies like Hadoop for making big data solutions more widely available is also covered.
Trendcasting for 2019 - What Will the Tuture of Tech HoldBrian Pichman
Join Brian Pichman of the Evolve Project as he highlights this year’s most significant technology trends and what it means for 2019. What changes are on the horizon? What technologies falling to the wayside? What technologies are on the verge of significant changes? What technologies should we expect to see flourish in the upcoming year?
The document discusses the initiation and integration of artificial intelligence in medical schools and colleges. It provides an overview of how medicine is changing with advancements in AI and machine learning, which are reshaping how doctors practice. It also examines the role of AI in medical education, with many seeing it as an assistive tool that can improve access to information for physicians and help make more accurate diagnoses. Concerns about reduced need for doctors and unemployment for students are mentioned but most see AI as a partner rather than a replacement for human physicians.
Potential use cases for use of Big Data in Pharma R&D. Also trying to take some of the hype out of the topic and present some tools that can be used to link and analyse data eventhough they are not really Big data (just important data)
Fru 2022 | Tech Trends, Themes, Thoughts, Perspectives and PredictionsFru Louis
1. The document discusses 10 top technology trends for 2022, including industry data cloud and marketplace, composable applications, and hyper-convergence.
2. It also covers auto-everything, privacy-enhancing computing, remote natives, generalized language models, antifragile systems, operational excellence, and DARQ power.
3. The document is authored by Fru Nde and provides perspectives on emerging technologies as well as information about the author's background, publications, and mission to empower and inspire others.
The document discusses the nature of data driven service innovation. Some key points made include:
- Data driven service innovation aims to create new services by finding innovative uses of data, but this process is messy and experimental as requirements are poorly defined initially.
- Big data projects resemble research more than production, requiring agility to combine conventional project management with an ability to fail fast and learn from mistakes.
- The complexity of modern ICT systems makes perfect causal understanding impossible. We must acknowledge our ignorance and use a probe-sense-analyze-act approach.
- Developing services is challenging as the customer experience is co-created and hard to define formally. Operational staff closest to customers provide important insights.
The document discusses the 60th anniversary of CCITT/ITU-T and artificial intelligence. It notes that 10 mobile/cloud companies achieving $4 trillion in market cap and that China's AI market is $337 billion. It discusses how AI is driving unprecedented changes through hyper time compression of innovations and extreme convergence across multiple domains. AI is also helping to track progress on the UN's Sustainable Development Goals. The ITU is partnering with IBM Watson on AI initiatives and standards are being discussed. Overall, the document outlines how AI is massively impacting the economy, society and driving disruption through new technologies.
This document provides an overview of how artificial intelligence and deep learning are revolutionizing various industries. It discusses key concepts like artificial intelligence, machine learning, and deep learning. It then highlights several use cases across healthcare, automotive, retail, and financial services. For example, it describes how deep learning has helped reduce error rates in breast cancer diagnosis by 85% and how AI is enabling more efficient warehouse operations and personalized shopping. The document concludes by offering advice on getting started with deep learning projects.
The success of an organization increasingly depends on their ability to draw conclusions regarding the various types of data available. Staying ahead of competitors requires many times to identify a trend, problem or opportunity microseconds before anyone else. That's why organizations must be able to analyze this information if they want to find insights that will help them to identify new opportunities underlying this phenomenon.
People are spontaneously uploading large amounts of information on the internet and this represents a great opportunity for companies to segment according to their behavior and not only socio-demographic factors. Companies store transactional information from their customers by making them fill in forms but the challenge for brands is to enrich these databases with information describing their customer’s behavior and daily habits. This info can be obtained through the online conversation and can be processed, crossed and enriched with many other types of information through different models based on Big Data. Following this procedure, we can complement the information we already have from our customers without having to ask them directly and therefor providing more value-added proposals to clients from a brand perspective.
Using the same technology with the right platform and the correct tactic, companies can achieve more ambitious goals that provide valuable information for the brand, which in turn could also enrich the customer’s experience, improving the customer journey for all types of clients.
less
The crusade for big data in the AAL domainAALForum
This document summarizes a keynote presentation about big data integration in the context of drug discovery. It discusses challenges with integrating diverse data sources, including issues with data volume, variety, veracity, and velocity. It presents the Open PHACTS platform as a case study, which integrates multiple biomedical databases into a single access point using semantic web technologies. Open PHACTS has developed apps and APIs to enable complex queries across integrated data related to diseases, tissues, targets, compounds and pathways. The talk highlights ongoing work to address issues like data licensing, identity resolution, quantitative data standards, quality assurance, and data provenance tracking in big data integration efforts.
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.aiSri Ambati
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/ZrlJQqNaSMI.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://www.twitter.com/h2oai.
This whitepaper provides an overview of artificial intelligence (AI) and its commercialization. It discusses the history and development of AI from early pattern recognition (AI 1.0) to today's deep learning (AI 2.0) to the emerging contextual reasoning (AI 3.0). Key points include how transfer learning and increased computing power are driving new AI applications and how AI is being applied commercially in healthcare, manufacturing, logistics, and other industries. The document also addresses the global demand for AI talent and the challenges of developing reliable AI systems that can operate under changing conditions.
The REAL Impact of Big Data on PrivacyClaudiu Popa
The awesome promise of Big Data is tempered by the need to protect personal information. Data scientists must expertly navigate the legislative waters and acquire the skills to protect privacy and security. This talk provides enterprise leaders with answers and suggests questions to ask when the time comes to consider the vast opportunities offered by big data.
This document discusses the key elements of innovative cultures, including personal engagement, openness, design thinking, rapid experimentation, leveraging platforms, evidence-based decision making, and psychological safety. It provides examples of how companies like IDEO, Pixar, and Amazon exemplify these principles and promotes applying design thinking techniques to develop innovations through activities like designing an ideal wallet. The goal is to help readers understand how to foster innovative cultures and take next steps to evaluate methods and share experiences.
The document discusses the new "ABC" of information and communication technologies (ICTs) in organizations. It argues that ICTs are playing an increasingly strategic role in today's competitive innovation context. Specifically, it claims that organizational success depends on two foundations: (1) new technologies on the global technological frontier and (2) new global business models and technologies. It suggests that companies must prepare for the complex challenges of the "Third Platform" driven by analytics, big data, and cloud computing.
ITCamp 2018 - Magnus Mårtensson - Azure Global Application PerspectivesITCamp
Building and running a service for a truly global audience has always been the ultimate challenge for any business and for any application developer. In this session, we will discuss global perspectives on running your application tier in a scalable way – WebApps/APIs, Traffic Manager and Serverless. We will discuss the new Cosmos DB service offering in Azure and it’s built in global sync with little more than a press of a button on your end – data was always the final frontier of globalization of your app. We will look at what it takes to monitor this kind of an environment. Naturally this is a very big set of topics which means this session is aimed to give an overview, spark a discussion and provide some directional and inspirational input.
This document discusses how crowdsourcing and big data are changing healthcare. It provides Wikipedia as an example of how crowdsourcing has been used to build the largest online encyclopedia through collaborative contributions. The document also discusses how places like TED provide freely accessible knowledge on the internet and how this is impacting fields like healthcare. It introduces concepts like the "infinite monkey theorem" to illustrate how crowdsourcing approaches can achieve results that traditionally required formal organizations and significant resources.
Diginomica 2019 2020 not ai neil raden article links and captionsNeil Raden
The balance of my articles on Diginomica 2019-2020other than AI: HPC/Supercomputers, Quantum, Cognitive, Complexity, Supply Chain, IoT, Edge Intelligence, Data, Telemedicine, healthcare Industry, For Good
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJSherry Jones
This article discusses how people's fears about big data may stem from their "old brain" instincts rather than rational thinking. It argues that while big data collection raises valid privacy concerns, the technology also has great potential to improve lives if used appropriately. The article urges focusing on positive applications and ensuring data is only used for beneficial purposes, rather than opposing big data due to hypothetical fears.
From Crowdsourcing to BigData - how ePatients, and their machines, are transf...Ferdinando Scala
Ferdinando Scala - Leandro Agrò
Today oceans of data are being produced and collected both by people and machines, at the same time changing the way we think about healthcare as a field of study; as a result Patients - actually ePatients - are becoming ever more informed and independent with their healthcare decisions.
Deep learning is the fastest growing field in artificial intelligence according to Gartner's top strategic technology trends for 2017 which ranks AI and machine learning as number one. The document then provides examples of how deep learning is accelerating innovation in various industries such as cancer research, speech recognition, and more. It promotes NVIDIA's deep learning and AI solutions to help readers learn how these technologies can impact their own business.
Introduction to Data Mining, Business Intelligence and Data ScienceIMC Institute
This document discusses data mining, business intelligence, and data science. It begins with an introduction to data mining, defining it as the application of algorithms to extract patterns from data. Business intelligence is defined as applications, infrastructure, tools, and practices that enable access to and analysis of information to improve decisions and performance. Data science is related to data mining, analytics, machine learning, and uses techniques from statistics and computer science to discover patterns in large datasets. The document provides examples of how data is used in areas like understanding customers, healthcare, sports, and financial trading.
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
Promoting Wellbeing - Applied Social Psychology - Psychology SuperNotesPsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
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Similar to Genomics Big Data: the need for Public-Private Partnership and innovative Cloud-based solutions
Fru 2022 | Tech Trends, Themes, Thoughts, Perspectives and PredictionsFru Louis
1. The document discusses 10 top technology trends for 2022, including industry data cloud and marketplace, composable applications, and hyper-convergence.
2. It also covers auto-everything, privacy-enhancing computing, remote natives, generalized language models, antifragile systems, operational excellence, and DARQ power.
3. The document is authored by Fru Nde and provides perspectives on emerging technologies as well as information about the author's background, publications, and mission to empower and inspire others.
The document discusses the nature of data driven service innovation. Some key points made include:
- Data driven service innovation aims to create new services by finding innovative uses of data, but this process is messy and experimental as requirements are poorly defined initially.
- Big data projects resemble research more than production, requiring agility to combine conventional project management with an ability to fail fast and learn from mistakes.
- The complexity of modern ICT systems makes perfect causal understanding impossible. We must acknowledge our ignorance and use a probe-sense-analyze-act approach.
- Developing services is challenging as the customer experience is co-created and hard to define formally. Operational staff closest to customers provide important insights.
The document discusses the 60th anniversary of CCITT/ITU-T and artificial intelligence. It notes that 10 mobile/cloud companies achieving $4 trillion in market cap and that China's AI market is $337 billion. It discusses how AI is driving unprecedented changes through hyper time compression of innovations and extreme convergence across multiple domains. AI is also helping to track progress on the UN's Sustainable Development Goals. The ITU is partnering with IBM Watson on AI initiatives and standards are being discussed. Overall, the document outlines how AI is massively impacting the economy, society and driving disruption through new technologies.
This document provides an overview of how artificial intelligence and deep learning are revolutionizing various industries. It discusses key concepts like artificial intelligence, machine learning, and deep learning. It then highlights several use cases across healthcare, automotive, retail, and financial services. For example, it describes how deep learning has helped reduce error rates in breast cancer diagnosis by 85% and how AI is enabling more efficient warehouse operations and personalized shopping. The document concludes by offering advice on getting started with deep learning projects.
The success of an organization increasingly depends on their ability to draw conclusions regarding the various types of data available. Staying ahead of competitors requires many times to identify a trend, problem or opportunity microseconds before anyone else. That's why organizations must be able to analyze this information if they want to find insights that will help them to identify new opportunities underlying this phenomenon.
People are spontaneously uploading large amounts of information on the internet and this represents a great opportunity for companies to segment according to their behavior and not only socio-demographic factors. Companies store transactional information from their customers by making them fill in forms but the challenge for brands is to enrich these databases with information describing their customer’s behavior and daily habits. This info can be obtained through the online conversation and can be processed, crossed and enriched with many other types of information through different models based on Big Data. Following this procedure, we can complement the information we already have from our customers without having to ask them directly and therefor providing more value-added proposals to clients from a brand perspective.
Using the same technology with the right platform and the correct tactic, companies can achieve more ambitious goals that provide valuable information for the brand, which in turn could also enrich the customer’s experience, improving the customer journey for all types of clients.
less
The crusade for big data in the AAL domainAALForum
This document summarizes a keynote presentation about big data integration in the context of drug discovery. It discusses challenges with integrating diverse data sources, including issues with data volume, variety, veracity, and velocity. It presents the Open PHACTS platform as a case study, which integrates multiple biomedical databases into a single access point using semantic web technologies. Open PHACTS has developed apps and APIs to enable complex queries across integrated data related to diseases, tissues, targets, compounds and pathways. The talk highlights ongoing work to address issues like data licensing, identity resolution, quantitative data standards, quality assurance, and data provenance tracking in big data integration efforts.
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.aiSri Ambati
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/ZrlJQqNaSMI.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://www.twitter.com/h2oai.
This whitepaper provides an overview of artificial intelligence (AI) and its commercialization. It discusses the history and development of AI from early pattern recognition (AI 1.0) to today's deep learning (AI 2.0) to the emerging contextual reasoning (AI 3.0). Key points include how transfer learning and increased computing power are driving new AI applications and how AI is being applied commercially in healthcare, manufacturing, logistics, and other industries. The document also addresses the global demand for AI talent and the challenges of developing reliable AI systems that can operate under changing conditions.
The REAL Impact of Big Data on PrivacyClaudiu Popa
The awesome promise of Big Data is tempered by the need to protect personal information. Data scientists must expertly navigate the legislative waters and acquire the skills to protect privacy and security. This talk provides enterprise leaders with answers and suggests questions to ask when the time comes to consider the vast opportunities offered by big data.
This document discusses the key elements of innovative cultures, including personal engagement, openness, design thinking, rapid experimentation, leveraging platforms, evidence-based decision making, and psychological safety. It provides examples of how companies like IDEO, Pixar, and Amazon exemplify these principles and promotes applying design thinking techniques to develop innovations through activities like designing an ideal wallet. The goal is to help readers understand how to foster innovative cultures and take next steps to evaluate methods and share experiences.
The document discusses the new "ABC" of information and communication technologies (ICTs) in organizations. It argues that ICTs are playing an increasingly strategic role in today's competitive innovation context. Specifically, it claims that organizational success depends on two foundations: (1) new technologies on the global technological frontier and (2) new global business models and technologies. It suggests that companies must prepare for the complex challenges of the "Third Platform" driven by analytics, big data, and cloud computing.
ITCamp 2018 - Magnus Mårtensson - Azure Global Application PerspectivesITCamp
Building and running a service for a truly global audience has always been the ultimate challenge for any business and for any application developer. In this session, we will discuss global perspectives on running your application tier in a scalable way – WebApps/APIs, Traffic Manager and Serverless. We will discuss the new Cosmos DB service offering in Azure and it’s built in global sync with little more than a press of a button on your end – data was always the final frontier of globalization of your app. We will look at what it takes to monitor this kind of an environment. Naturally this is a very big set of topics which means this session is aimed to give an overview, spark a discussion and provide some directional and inspirational input.
This document discusses how crowdsourcing and big data are changing healthcare. It provides Wikipedia as an example of how crowdsourcing has been used to build the largest online encyclopedia through collaborative contributions. The document also discusses how places like TED provide freely accessible knowledge on the internet and how this is impacting fields like healthcare. It introduces concepts like the "infinite monkey theorem" to illustrate how crowdsourcing approaches can achieve results that traditionally required formal organizations and significant resources.
Diginomica 2019 2020 not ai neil raden article links and captionsNeil Raden
The balance of my articles on Diginomica 2019-2020other than AI: HPC/Supercomputers, Quantum, Cognitive, Complexity, Supply Chain, IoT, Edge Intelligence, Data, Telemedicine, healthcare Industry, For Good
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJSherry Jones
This article discusses how people's fears about big data may stem from their "old brain" instincts rather than rational thinking. It argues that while big data collection raises valid privacy concerns, the technology also has great potential to improve lives if used appropriately. The article urges focusing on positive applications and ensuring data is only used for beneficial purposes, rather than opposing big data due to hypothetical fears.
From Crowdsourcing to BigData - how ePatients, and their machines, are transf...Ferdinando Scala
Ferdinando Scala - Leandro Agrò
Today oceans of data are being produced and collected both by people and machines, at the same time changing the way we think about healthcare as a field of study; as a result Patients - actually ePatients - are becoming ever more informed and independent with their healthcare decisions.
Deep learning is the fastest growing field in artificial intelligence according to Gartner's top strategic technology trends for 2017 which ranks AI and machine learning as number one. The document then provides examples of how deep learning is accelerating innovation in various industries such as cancer research, speech recognition, and more. It promotes NVIDIA's deep learning and AI solutions to help readers learn how these technologies can impact their own business.
Introduction to Data Mining, Business Intelligence and Data ScienceIMC Institute
This document discusses data mining, business intelligence, and data science. It begins with an introduction to data mining, defining it as the application of algorithms to extract patterns from data. Business intelligence is defined as applications, infrastructure, tools, and practices that enable access to and analysis of information to improve decisions and performance. Data science is related to data mining, analytics, machine learning, and uses techniques from statistics and computer science to discover patterns in large datasets. The document provides examples of how data is used in areas like understanding customers, healthcare, sports, and financial trading.
Similar to Genomics Big Data: the need for Public-Private Partnership and innovative Cloud-based solutions (20)
Cell Therapy Expansion and Challenges in Autoimmune DiseaseHealth Advances
There is increasing confidence that cell therapies will soon play a role in the treatment of autoimmune disorders, but the extent of this impact remains to be seen. Early readouts on autologous CAR-Ts in lupus are encouraging, but manufacturing and cost limitations are likely to restrict access to highly refractory patients. Allogeneic CAR-Ts have the potential to broaden access to earlier lines of treatment due to their inherent cost benefits, however they will need to demonstrate comparable or improved efficacy to established modalities.
In addition to infrastructure and capacity constraints, CAR-Ts face a very different risk-benefit dynamic in autoimmune compared to oncology, highlighting the need for tolerable therapies with low adverse event risk. CAR-NK and Treg-based therapies are also being developed in certain autoimmune disorders and may demonstrate favorable safety profiles. Several novel non-cell therapies such as bispecific antibodies, nanobodies, and RNAi drugs, may also offer future alternative competitive solutions with variable value propositions.
Widespread adoption of cell therapies will not only require strong efficacy and safety data, but also adapted pricing and access strategies. At oncology-based price points, CAR-Ts are unlikely to achieve broad market access in autoimmune disorders, with eligible patient populations that are potentially orders of magnitude greater than the number of currently addressable cancer patients. Developers have made strides towards reducing cell therapy COGS while improving manufacturing efficiency, but payors will inevitably restrict access until more sustainable pricing is achieved.
Despite these headwinds, industry leaders and investors remain confident that cell therapies are poised to address significant unmet need in patients suffering from autoimmune disorders. However, the extent of this impact on the treatment landscape remains to be seen, as the industry rapidly approaches an inflection point.
Promoting Wellbeing - Applied Social Psychology - Psychology SuperNotesPsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of the physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar lead (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
6. Describe the flow of current around the heart during the cardiac cycle
7. Discuss the placement and polarity of the leads of electrocardiograph
8. Describe the normal electrocardiograms recorded from the limb leads and explain the physiological basis of the different records that are obtained
9. Define mean electrical vector (axis) of the heart and give the normal range
10. Define the mean QRS vector
11. Describe the axes of leads (hexagonal reference system)
12. Comprehend the vectorial analysis of the normal ECG
13. Determine the mean electrical axis of the ventricular QRS and appreciate the mean axis deviation
14. Explain the concepts of current of injury, J point, and their significance
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. Chapter 3, Cardiology Explained, https://www.ncbi.nlm.nih.gov/books/NBK2214/
7. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
ABDOMINAL TRAUMA in pediatrics part one.drhasanrajab
Abdominal trauma in pediatrics refers to injuries or damage to the abdominal organs in children. It can occur due to various causes such as falls, motor vehicle accidents, sports-related injuries, and physical abuse. Children are more vulnerable to abdominal trauma due to their unique anatomical and physiological characteristics. Signs and symptoms include abdominal pain, tenderness, distension, vomiting, and signs of shock. Diagnosis involves physical examination, imaging studies, and laboratory tests. Management depends on the severity and may involve conservative treatment or surgical intervention. Prevention is crucial in reducing the incidence of abdominal trauma in children.
- Video recording of this lecture in English language: https://youtu.be/kqbnxVAZs-0
- Video recording of this lecture in Arabic language: https://youtu.be/SINlygW1Mpc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Rasamanikya is a excellent preparation in the field of Rasashastra, it is used in various Kushtha Roga, Shwasa, Vicharchika, Bhagandara, Vatarakta, and Phiranga Roga. In this article Preparation& Comparative analytical profile for both Formulationon i.e Rasamanikya prepared by Kushmanda swarasa & Churnodhaka Shodita Haratala. The study aims to provide insights into the comparative efficacy and analytical aspects of these formulations for enhanced therapeutic outcomes.
Genomics Big Data: the need for Public-Private Partnership and innovative Cloud-based solutions
1. Genomics Big Data: the need for Public-
Private Partnership and innovative Cloud-
based solutions
Rodrigo Jardim
Alberto M. R. Dávila
Computational and Systems Biology Laboratory, Instituto
Oswaldo Cruz, FIOCRUZ
amrdavila