The presentation aims at raising the regulatory awareness of human reproduction healthcare professionals, introduce tools and techniques that can help them on regulatory journey and avoid pitfalls.
AI Safety and Regulations Navigating the Post COVID Era Aims, Opportunities, ...ijtsrd
Artificial Intelligence AI has become an integral part of our post COVID world, influencing various aspects of our lives, from healthcare to remote work and education. While AI offers numerous advantages, it also poses significant risks, including ethical dilemmas, bias, privacy concerns, and potential job displacement. This abstract explores the evolving landscape of AI safety and regulations in the wake of the COVID 19 pandemic. AI safety encompasses efforts to ensure that AI systems are developed and deployed responsibly, preventing unintended consequences and safeguarding individuals and society at large. In parallel, AI regulations aim to establish a framework that guides the ethical and accountable use of AI technologies. These regulations address data privacy, bias mitigation, transparency, and accountability, among other critical aspects. The advantages of AI safety and regulation are evident in their capacity to protect public health, privacy, and fairness. In healthcare, they ensure the accuracy of diagnostic AI systems and safeguard patient data. In remote work and education, they promote equitable access to AI enhanced services. Additionally, AI safety and regulation play a crucial role in supply chain resilience, mental health support, and the development of digital health records and vaccine passports. However, several limitations and challenges need to be acknowledged. Rapid technological advancements often outpace regulatory frameworks, making it challenging to maintain relevance. Global variations in regulations can create complexities for international cooperation. Overregulation can stifle innovation, while a lack of enforcement can render regulations toothless. The future trends in AI safety and regulation will be shaped by the lessons learned from the COVID 19 pandemic. We anticipate global collaboration and standardization efforts, the proliferation of ethical AI frameworks, and sector specific regulations. Transparent AI, accountability laws, and adaptive regulations will play a significant role in shaping the responsible development and deployment of AI technologies. In conclusion, AI safety and regulation are essential components of a post COVID world that seeks to harness the benefits of AI while mitigating its potential risks. The responsible development and use of AI technologies are crucial in ensuring a secure, equitable, and ethical digital future. Manish Verma "AI Safety and Regulations: Navigating the Post-COVID Era: Aims, Opportunities, and Challenges: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-6 , December 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60087.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/60087/ai-safety-and-regulations-navigating-the-postcovid-era-aims-opportunities-and-challenges-a-chatgpt-analysis/manish-verma
This document discusses the Internet of Medical Things (IoMT) and securing medical devices in an increasingly connected world. It provides background on the growing number of connected medical devices and emerging issues around cybersecurity and privacy. The document outlines some key challenges around regulating and securing medical devices as well as establishing trust and developing best practices for an end-to-end security architecture for the IoMT. It argues that device designers, manufacturers and service providers need to ensure the security and privacy of customer data to meet legal requirements and maintain trust.
Improving Efficiency and Outcomes in Healthcare using Internet of ThingsCitiusTech
With the adoption of cloud and big data technologies, healthcare organizations are in a position to begin experimenting with IoT. Ranging from home care to smart facilities, there are many ways in which provider organizations can benefit by using IoT in their patient care workflows. E.g., a mobile app with patient geo-fencing capabilities can help optimize physician rounds by dynamically routing the physician to the nearest patient
Payers can leverage insights generated by IoT infrastructure to improve population health, increase patient awareness and reduce healthcare costs. Payers can also design more effective reward and retention programs using IoT generated data.
As IoT is evolving, adoption is slow but steady, and investments are being made by both startups and industry leaders. Healthcare is among the top 5 industries investing in IoT.
This document discusses how IoT can be leveraged to drive efficiency in healthcare workflows and enhance clinical outcomes.
This document discusses the use of artificial intelligence and machine learning techniques for chronic disease detection and management. It provides background on chronic diseases and their impact globally. It then discusses how machine learning algorithms can be used to analyze medical data from electronic health records to predict chronic diseases and suggest treatments. Various studies that have developed models using techniques like decision trees, neural networks, and random forests to detect diseases like cancer, kidney disease and diabetes are summarized. The ability of artificial intelligence to help diagnose chronic diseases earlier and improve healthcare management is also mentioned.
Through practical case studies and industry specific analysis sessions, Medical Device UDIs & Traceability Forum Europe 2015 is geared around strengthening your regulatory infrastructure, maintaining productivity and ensuring ROI from your UDI projects.
View the full agenda here: bit.ly/MedicalDeviceUDI2015Agenda
Alternatively, email enquire@iqpc.co.uk or call +44 (0)207 036 1300 for a copy.
Steve Wood Generative AI and Data Protection Asia Privacy Bridge October 202...stevewood900540
This document discusses generative AI, data protection laws, and the challenges posed by generative models. It outlines how generative AI can use personal data from training and during use. It also summarizes the data protection risks, compliance measures taken by developers, and actions taken by regulators. Regulators have expressed concerns about transparency, children's data, rights, and more. Looking ahead, more guidance and regulatory actions are expected regarding generative AI and the supply chain.
The emergence of the Internet of things has attracted the attention of governments, research scholars, healthcare, and business community all over the world. In the healthcare system, the motivation for using IoT is to offer promising solutions for efficiently delivering all kinds of medical healthcare services to patients at an affordable cost. IoT could be a game changer for healthcare services. It makes it now possible to process data and remotely monitor a patient in real time. IoT is important in healthcare because of the services it provides. These services enhance the quality and efficiency of care treatments which benefit patients, doctors, nurses, and hospitals in a great way. This chapter covers various applications of IoT in healthcare and their benefits and challenges. Matthew N. O. Sadiku | Uwakwe C. Chukwu | Abayomi Ajayi-Majebi | Sarhan M. Musa "Applications of IoT in Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49675.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/49675/applications-of-iot-in-healthcare/matthew-n-o-sadiku
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
AI Safety and Regulations Navigating the Post COVID Era Aims, Opportunities, ...ijtsrd
Artificial Intelligence AI has become an integral part of our post COVID world, influencing various aspects of our lives, from healthcare to remote work and education. While AI offers numerous advantages, it also poses significant risks, including ethical dilemmas, bias, privacy concerns, and potential job displacement. This abstract explores the evolving landscape of AI safety and regulations in the wake of the COVID 19 pandemic. AI safety encompasses efforts to ensure that AI systems are developed and deployed responsibly, preventing unintended consequences and safeguarding individuals and society at large. In parallel, AI regulations aim to establish a framework that guides the ethical and accountable use of AI technologies. These regulations address data privacy, bias mitigation, transparency, and accountability, among other critical aspects. The advantages of AI safety and regulation are evident in their capacity to protect public health, privacy, and fairness. In healthcare, they ensure the accuracy of diagnostic AI systems and safeguard patient data. In remote work and education, they promote equitable access to AI enhanced services. Additionally, AI safety and regulation play a crucial role in supply chain resilience, mental health support, and the development of digital health records and vaccine passports. However, several limitations and challenges need to be acknowledged. Rapid technological advancements often outpace regulatory frameworks, making it challenging to maintain relevance. Global variations in regulations can create complexities for international cooperation. Overregulation can stifle innovation, while a lack of enforcement can render regulations toothless. The future trends in AI safety and regulation will be shaped by the lessons learned from the COVID 19 pandemic. We anticipate global collaboration and standardization efforts, the proliferation of ethical AI frameworks, and sector specific regulations. Transparent AI, accountability laws, and adaptive regulations will play a significant role in shaping the responsible development and deployment of AI technologies. In conclusion, AI safety and regulation are essential components of a post COVID world that seeks to harness the benefits of AI while mitigating its potential risks. The responsible development and use of AI technologies are crucial in ensuring a secure, equitable, and ethical digital future. Manish Verma "AI Safety and Regulations: Navigating the Post-COVID Era: Aims, Opportunities, and Challenges: A ChatGPT Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-6 , December 2023, URL: https://www.ijtsrd.com/papers/ijtsrd60087.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/60087/ai-safety-and-regulations-navigating-the-postcovid-era-aims-opportunities-and-challenges-a-chatgpt-analysis/manish-verma
This document discusses the Internet of Medical Things (IoMT) and securing medical devices in an increasingly connected world. It provides background on the growing number of connected medical devices and emerging issues around cybersecurity and privacy. The document outlines some key challenges around regulating and securing medical devices as well as establishing trust and developing best practices for an end-to-end security architecture for the IoMT. It argues that device designers, manufacturers and service providers need to ensure the security and privacy of customer data to meet legal requirements and maintain trust.
Improving Efficiency and Outcomes in Healthcare using Internet of ThingsCitiusTech
With the adoption of cloud and big data technologies, healthcare organizations are in a position to begin experimenting with IoT. Ranging from home care to smart facilities, there are many ways in which provider organizations can benefit by using IoT in their patient care workflows. E.g., a mobile app with patient geo-fencing capabilities can help optimize physician rounds by dynamically routing the physician to the nearest patient
Payers can leverage insights generated by IoT infrastructure to improve population health, increase patient awareness and reduce healthcare costs. Payers can also design more effective reward and retention programs using IoT generated data.
As IoT is evolving, adoption is slow but steady, and investments are being made by both startups and industry leaders. Healthcare is among the top 5 industries investing in IoT.
This document discusses how IoT can be leveraged to drive efficiency in healthcare workflows and enhance clinical outcomes.
This document discusses the use of artificial intelligence and machine learning techniques for chronic disease detection and management. It provides background on chronic diseases and their impact globally. It then discusses how machine learning algorithms can be used to analyze medical data from electronic health records to predict chronic diseases and suggest treatments. Various studies that have developed models using techniques like decision trees, neural networks, and random forests to detect diseases like cancer, kidney disease and diabetes are summarized. The ability of artificial intelligence to help diagnose chronic diseases earlier and improve healthcare management is also mentioned.
Through practical case studies and industry specific analysis sessions, Medical Device UDIs & Traceability Forum Europe 2015 is geared around strengthening your regulatory infrastructure, maintaining productivity and ensuring ROI from your UDI projects.
View the full agenda here: bit.ly/MedicalDeviceUDI2015Agenda
Alternatively, email enquire@iqpc.co.uk or call +44 (0)207 036 1300 for a copy.
Steve Wood Generative AI and Data Protection Asia Privacy Bridge October 202...stevewood900540
This document discusses generative AI, data protection laws, and the challenges posed by generative models. It outlines how generative AI can use personal data from training and during use. It also summarizes the data protection risks, compliance measures taken by developers, and actions taken by regulators. Regulators have expressed concerns about transparency, children's data, rights, and more. Looking ahead, more guidance and regulatory actions are expected regarding generative AI and the supply chain.
The emergence of the Internet of things has attracted the attention of governments, research scholars, healthcare, and business community all over the world. In the healthcare system, the motivation for using IoT is to offer promising solutions for efficiently delivering all kinds of medical healthcare services to patients at an affordable cost. IoT could be a game changer for healthcare services. It makes it now possible to process data and remotely monitor a patient in real time. IoT is important in healthcare because of the services it provides. These services enhance the quality and efficiency of care treatments which benefit patients, doctors, nurses, and hospitals in a great way. This chapter covers various applications of IoT in healthcare and their benefits and challenges. Matthew N. O. Sadiku | Uwakwe C. Chukwu | Abayomi Ajayi-Majebi | Sarhan M. Musa "Applications of IoT in Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49675.pdf Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/49675/applications-of-iot-in-healthcare/matthew-n-o-sadiku
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
KARE – A Patent Protected AI based Technology into Hospital and Healthcare IIJSRJournal
Artificial Intelligence (AI) is a technology that, when linked with healthcare apps and smart wearable devices, can anticipate the onset of health issues in users by gathering and analyzing their health data. The integration of AI with smart wearable devices offers a wide range of potential applications in smart healthcare, however there is an issue with the black box operation of AI models' judgments, which has led in a lack of accountability and trust in the decisions made. In the field of healthcare, transparency, outcome tracing, and model improvement are all important. Healthcare providers can be more watchful and proactive in their interactions with patients thanks to the Internet of Things. Wheelchairs, defibrillators, nebulizers, oxygen pumps, and other monitoring devices are all tracked in real time utilizing IoT devices with sensors.
Big data analytics and internet of things for personalised healthcare: opport...IJECEIAES
With the increasing use of technologies and digitally driven healthcare systems worldwide, there will be several opportunities for the use of big data in personalized healthcare. In addition, With the advancements and availability of internet of things (IoT) based point-of-care (POC) technologies, big data analytics and artificial intelligence (AI) can provide useful methods and solutions in monitoring, diagnosis, and self-management of health issues for a better personalized healthcare. In this paper, we identify the current personalized healthcare trends and challenges. Then, propose an architecture to support big data analytics using POC test results of an individual. The proposed architecture can facilitate an integrated and self-managed healthcare as well as remote patient care by adapting three popular machine learning algorithms to leverage the current trends in IoT, big data infrastructures and data analytics for advancing personalized healthcare of the future.
Wearable technologies and remote patient remote monitoring systemGiulio Coraggio
The document summarizes a webinar presentation about legal issues related to patient remote monitoring systems and wearable technologies in healthcare. Remote patient monitoring allows patients to perform routine medical tests and send results to healthcare providers in real-time using mobile devices. Key legal issues discussed include privacy regulations around collection and processing of patient data, potential qualification of hardware and software as medical devices, and intellectual property protection of the monitoring technologies.
Patient remote monitoring system in Wearable TechnologyMike Evans
The document summarizes a webinar discussing legal issues related to patient remote monitoring systems and wearable technologies in healthcare. Remote patient monitoring allows patients to perform routine medical tests and send results to healthcare providers in real-time using mobile devices. Key legal issues addressed include privacy regulations around collection and processing of patient data, qualification of hardware and software as medical devices, and intellectual property protection of the monitoring technologies.
An Analysis on IoT Methodologies for Smart Health Care and Surgical Treatment...ijtsrd
This document discusses the use of Internet of Things (IoT) methodologies and haptic interfaces for smart healthcare and surgical treatment. It begins by defining haptics as the science of applying touch sensation and control to interactions with computers. It then outlines how IoT and haptics can benefit patients, doctors, clinics, and medical insurance companies through remote health monitoring, improved treatment decisions, reduced costs, and more efficient processes. The document also examines the four stages of an IoT architecture and reviews current literature on incorporating haptics into areas like surgical simulators. While IoT and haptics show potential for transforming healthcare, challenges remain regarding data security, privacy, and real-time analytics capabilities.
Data preparation for artificial intelligence in medical imaging - A comprehen...Daniel983829
This document provides a comprehensive guide to tools and platforms for preparing medical image data for artificial intelligence applications. It discusses key steps in a medical image preparation pipeline including image acquisition, de-identification, data curation, storage, and annotation. A variety of open-access tools are reviewed that can perform image de-identification, data curation, storage, and annotation. Examples of medical imaging datasets covering different organs and diseases are also provided. The guide aims to enable standardized and large-scale data preparation and AI development in medical imaging.
1) By 2023, the healthcare industry is expected to reach a plateau with major breakthroughs in high-technology innovations and discoveries that will transform medicine.
2) Integrated medical technologies using the internet are changing how hospitals communicate with patients and each other through tools like telemedicine, medical IoT devices, and AI integrated with traditional devices.
3) Surgical robots like the Da Vinci system are becoming more common and can enable more precise and minimally invasive surgeries, though they also present risks like mechanical failures or accidental injuries if systems malfunction.
The Topic I choose was Wearable Sensor Technology based off this s.docxchristalgrieg
The Topic I choose was Wearable Sensor Technology based off this student’s paper below.
PLEASE DO NOT USE ANY INFORMATION FROM STUDENTS PAPER IN MY PAPER PLEASE.
Wearable Sensor Technology Draft
Wearable sensor technology is growing in the cybersecurity industry because of its detection, prevention and documentation aspect of the technology. Wearable sensor technology is anything on the human body that can be worn including clothing (Costa, Rodrigues, Silva, Isento, & Corchado, 2015). These devices are able to prevent, detect, document and react to other technology. They are used by different industries but can be found mostly in the healthcare industry. These devices can range from a smartwatch to a t-shirt that can track movements. Wearable sensor technology can be found all over the globe from business to being used at home to track personal fitness. A business that conducts their research and use wearable sensor technology has a leading edge over those that don’t.
Features and Capabilities
Wearable sensor biological technology is mostly to help the healthcare industry. Biosensors on the wearable technology are able to monitor vital signs of patients, athletes, children and even the elderly (Ajami & Teimouri, 2015). The sensors are able to read the body’s movement and send the information to the medical team to document their health information (Raths, 2015). The Apple Watch is an example of a biometric wearable device because it monitors steps being taken and calories burned (Elsevier, 2014). The Apple Watch could be used in the medical field and help patients that are in rehabilitation (Raths, 2015). Most wearable technologies have features like Wi-Fi, GPRS (General Packet Radio Services), Bluetooth, GPS (Global Positioning System), and third party applications (Costa et al., 2015).
Technology interactions with people / environments / processes
Wearable sensor technology is used for patients in hospitals, elderly in special care and athletes that are trying to track performance. For example, the Apple Watch will monitor someone’s steps and their movements throughout the day. Just because it monitors their movement doesn’t mean that the person will become healthier. Some people use this device to fight obesity (Drury, 2014). These types of devices are used as tools to recognize the user’s or patients abilities and weaknesses (Drury, 2014). Biological wearable technology can be used by anybody that is any age. These types of devices are not subject to one kind of person or skin type. Wearable technology is now making its way to access control points by being able to open doors to businesses (Everett, 2015).
Costs and Benefits
Wearable sensor technology in 2015 was up to $20 billion dollars (Ajami & Teimouri, 2015). The market is expected to rise at least $50 billion dollars in the next ten years (Ajami & Teimouri, 2015). Wearable technology is hard to implement because of the high costs so most small business are not able to aff ...
CINECA webinar slides: Status Update Code of Conduct: Teaming up & Talking ab...CINECAProject
Committed to the drafting of a Code of Conduct for the sector of health research according to Art. 40 GDPR, our initiative is advancing slowly but steadily. Throughout Europe, national jurisdictions differ to a great deal in their interpretations of the GDPR, especially in regard to its application in health research. This is due to some quite vague provisions (public interest, not incompatible clause) as wells as to numerous exemption/derogation clauses concerning the use of health data for research purposes, which encourage States to set up national rules – enhancing fragmentation. Notably, a Code of Conduct can help to bridge the harmonization gaps that may exist between Member States in their application of data protection law. On a practical level, a code is potentially a cost-effective method to achieve greater levels of consistency of protection as well as a mechanism to demonstrate compliance with the GDPR. By spring 2020, several hundred individuals representing around 90 organizations in the field of health research have indicated their interest and support for the Code of Conduct for Health Research. At this stage, this does not yet indicate an endorsement but means that they see a benefit in the development of such a code and are interested in partaking in the process. Additionally, several exchanges take place with national and sectoral codes in order to use synergies and finds ways for collaboration. This webinar is intended to inform you about the latest results.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 1st October 2020 and is part of the CINECA webinar series. It is best viewed in full screen mode using Google Chrome.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
IoT and Mobile Application Based Model for Healthcare Management Systemijtsrd
The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things IoT has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up to date summary of the potential healthcare applications of IoT HIoT based technologies. It is necessary to develop an innovative solution in the Smart Building context that increases guests’ hospitality level during the pandemics in locations like hotels, conference locations, campuses, and hospitals. The solution supports features intending to control the number of occupants by online appointments, smart navigation, and queue management in the building through mobile phones and navigation to the desired location by highlighting interests and facilities. Moreover, checking the space occupancy, and automatic adjustment of the environmental features are the abilities that can be added to the proposed design in the future development. The proposed solution can address all mentioned issues regarding the smart building by integrating and utilizing various data sources collected by the internet of things IoT sensors. Then, storing and processing collected data in servers and finally sending the desired information to the end users. Consequently, through the integration of multiple IoT technologies, a unique platform with minimal hardware usage and maximum adaptability for smart management of general and healthcare services in hospital buildings will be created. Dr. Rajendra Kumar Bharti "IoT and Mobile Application Based Model for Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd51889.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/51889/iot-and-mobile-application-based-model-for-healthcare-management-system/dr-rajendra-kumar-bharti
PharmaLedger Official Presentation OverviewPharmaLedger
Download the Official PharmaLedger Project presentation, which introduces the project, its organisation and summarises the use cases.
In this downloadable presentation, you can find:
An introduction to the PharmaLedger project
PharmaLedger consortium
PharmaLedger objectives
Project organisation and governance
PharmaLedger platform overview
PharmaLedger selected use cases
Project roadmap
Value chain of use cases
Clinical Supply Chain Traceability use case summary
Supply Chain – Finished Goods Traceability use case summary
Supply Chain – E-Leaflet | EPI use case summary
Supply Chain – Anti-Counterfeiting use case summary
Clinical Trial – E-Consent use case summary
Healthdata – Medical Device IoT use case summary
Clinical Trial – Recruitment use case summary
Healthdata – Personalised Medicine use case summary
--
This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 853992. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
Disclaimer: Any information on this presentation solely reflects the author’s view and neither IMI nor the European Union or EFPIA are responsible for any use that may be made of the information contained herein.
The document discusses that artificial intelligence will drive the fourth industrial revolution and transform many jobs and industries over the next decade. It provides examples of generative AI technologies that can actively generate results for users in areas like image creation, music generation, and video production. The document also discusses challenges that may arise from increased use of AI, like job losses, and how companies can make decisions using internal corporate data and AI.
AI, IoMT and Blockchain in Healthcare.pdfrectified
This document discusses the application of artificial intelligence, internet of medical things, and blockchain technology in healthcare. Specifically, it covers:
1) How AI, IoMT, and blockchain can enhance patient outcomes, reduce costs, and improve efficiencies in healthcare.
2) Examples of current applications of these technologies, including in breast cancer diagnosis, PCOS diagnosis, and dementia detection. Machine learning algorithms are shown to outperform humans in some medical image analysis and diagnosis tasks.
3) Challenges and future research areas around implementing these technologies, such as ensuring patient privacy and data security.
AI in healthcare has several strengths like telemedicine, drug discovery, and personalized medicine. However, it also faces weaknesses such as data privacy issues and slow learning. Opportunities include reduced costs, 24/7 availability, and faster data analysis. Threats involve bias, job losses, and regulatory hurdles. Ethical challenges pertain to accuracy, overestimating benefits, and unjustified expenses. Considerations around context appropriateness, infrastructure requirements, and avoidance of harms like stigmatization are also important.
FEDERAL LEARNING BASED SOLUTIONS FOR PRIVACY AND ANONYMITY IN INTERNET OF MED...IRJET Journal
This document discusses the use of federated learning (FL) for privacy-preserving analysis of medical data from internet of things (IoT) devices. FL allows decentralized training of machine learning models on devices without moving sensitive patient data to a central location. The rise of IoT in healthcare is generating huge volumes of data but current AI approaches require aggregating data, raising privacy and security concerns. FL emerges as a solution by enabling decentralized and collaborative training while keeping data on devices. The document reviews literature on applying FL to clinical IoT applications and discusses how FL can address data isolation issues and perform AI tasks without compromising privacy.
The document is a code of practice for consumer IoT security that provides 13 guidelines for securing internet-connected devices and associated services. The guidelines address issues such as using unique passwords instead of defaults, keeping software updated, securely storing credentials, encrypting communications, and making it easy for consumers to delete personal data. The aim is to support all parties in developing secure consumer IoT products and services.
Enablers for IoT regarding Wearable Medical Devices to Support Healthy Living...Dr. Mustafa Değerli
This document discusses enablers for the Internet of Things (IoT) regarding wearable medical devices to support healthy living. It conducted a study using a questionnaire distributed to 511 wearable medical device users. Through exploratory factor analysis, it identified five key enablers with 17 total items: 1) Dependability, 2) Design, 3) Worthiness, 4) Privacy, confidentiality and security, and 5) Compatibility. The study provides a checklist for stakeholders to evaluate devices and identify areas for improvement to increase success and adoption of IoT-enabled wearable medical technologies.
IRJET- A Comprehensive Survey on Smart Healthcare Monitoring of Patients usin...IRJET Journal
This document summarizes a research paper that conducted a comprehensive survey on using the Internet of Things (IoT) for smart healthcare monitoring of patients. The key aspects covered are:
1) IoT enables remote patient monitoring through wearable devices that allow healthcare professionals to monitor patients' conditions without being physically present.
2) The survey reviewed various existing works on IoT-based remote patient monitoring systems that transmit patients' health data like temperature and oxygen levels to doctors via wireless networks and mobile apps.
3) Ensuring patient privacy and security while monitoring and accessing health data remotely is an important challenge addressed in some of the existing research.
VeriTeQ provides proprietary healthcare solutions including implantable radio frequency microchip technology cleared by the FDA. The document discusses VeriTeQ's unique value in enabling compliance with an FDA Final Rule requiring medical devices to carry a direct part marking through automatic identification and data capture technology. It also summarizes VeriTeQ's product portfolio in medical device identification, bio-sensing technologies, target markets, and financial projections showing significant revenue growth potential over the next five years.
This document provides an overview of consumer healthtech and discusses the personal information it collects and processes. It notes that consumer healthtech includes wearable devices and apps that track health metrics. It states these technologies collect sensitive data like heart rate, sleep quality, and potentially biomarkers from tears or sweat. The document discusses how this data is initially collected locally by devices but then sent to cloud servers for further processing using AI. It notes potential privacy risks if this health data is leaked, used for unsuitable purposes, or to make inappropriate health decisions about individuals.
APIs, data formats and the growing might of FHIRVlad Stirbu
This document discusses the evolution of data exchange standards in healthcare over time, from early messaging formats like HL7 to current standards like FHIR and DICOM. It notes the rise of consumer wearables and cloud computing. FHIR is presented as the current gold standard for exchanging healthcare data via APIs. The document cautions that when building healthcare software, one must pay attention to regulations from bodies like the FDA and considerations around intended use, operations in the cloud, and following quality processes.
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The document summarizes a webinar presentation about legal issues related to patient remote monitoring systems and wearable technologies in healthcare. Remote patient monitoring allows patients to perform routine medical tests and send results to healthcare providers in real-time using mobile devices. Key legal issues discussed include privacy regulations around collection and processing of patient data, potential qualification of hardware and software as medical devices, and intellectual property protection of the monitoring technologies.
Patient remote monitoring system in Wearable TechnologyMike Evans
The document summarizes a webinar discussing legal issues related to patient remote monitoring systems and wearable technologies in healthcare. Remote patient monitoring allows patients to perform routine medical tests and send results to healthcare providers in real-time using mobile devices. Key legal issues addressed include privacy regulations around collection and processing of patient data, qualification of hardware and software as medical devices, and intellectual property protection of the monitoring technologies.
An Analysis on IoT Methodologies for Smart Health Care and Surgical Treatment...ijtsrd
This document discusses the use of Internet of Things (IoT) methodologies and haptic interfaces for smart healthcare and surgical treatment. It begins by defining haptics as the science of applying touch sensation and control to interactions with computers. It then outlines how IoT and haptics can benefit patients, doctors, clinics, and medical insurance companies through remote health monitoring, improved treatment decisions, reduced costs, and more efficient processes. The document also examines the four stages of an IoT architecture and reviews current literature on incorporating haptics into areas like surgical simulators. While IoT and haptics show potential for transforming healthcare, challenges remain regarding data security, privacy, and real-time analytics capabilities.
Data preparation for artificial intelligence in medical imaging - A comprehen...Daniel983829
This document provides a comprehensive guide to tools and platforms for preparing medical image data for artificial intelligence applications. It discusses key steps in a medical image preparation pipeline including image acquisition, de-identification, data curation, storage, and annotation. A variety of open-access tools are reviewed that can perform image de-identification, data curation, storage, and annotation. Examples of medical imaging datasets covering different organs and diseases are also provided. The guide aims to enable standardized and large-scale data preparation and AI development in medical imaging.
1) By 2023, the healthcare industry is expected to reach a plateau with major breakthroughs in high-technology innovations and discoveries that will transform medicine.
2) Integrated medical technologies using the internet are changing how hospitals communicate with patients and each other through tools like telemedicine, medical IoT devices, and AI integrated with traditional devices.
3) Surgical robots like the Da Vinci system are becoming more common and can enable more precise and minimally invasive surgeries, though they also present risks like mechanical failures or accidental injuries if systems malfunction.
The Topic I choose was Wearable Sensor Technology based off this s.docxchristalgrieg
The Topic I choose was Wearable Sensor Technology based off this student’s paper below.
PLEASE DO NOT USE ANY INFORMATION FROM STUDENTS PAPER IN MY PAPER PLEASE.
Wearable Sensor Technology Draft
Wearable sensor technology is growing in the cybersecurity industry because of its detection, prevention and documentation aspect of the technology. Wearable sensor technology is anything on the human body that can be worn including clothing (Costa, Rodrigues, Silva, Isento, & Corchado, 2015). These devices are able to prevent, detect, document and react to other technology. They are used by different industries but can be found mostly in the healthcare industry. These devices can range from a smartwatch to a t-shirt that can track movements. Wearable sensor technology can be found all over the globe from business to being used at home to track personal fitness. A business that conducts their research and use wearable sensor technology has a leading edge over those that don’t.
Features and Capabilities
Wearable sensor biological technology is mostly to help the healthcare industry. Biosensors on the wearable technology are able to monitor vital signs of patients, athletes, children and even the elderly (Ajami & Teimouri, 2015). The sensors are able to read the body’s movement and send the information to the medical team to document their health information (Raths, 2015). The Apple Watch is an example of a biometric wearable device because it monitors steps being taken and calories burned (Elsevier, 2014). The Apple Watch could be used in the medical field and help patients that are in rehabilitation (Raths, 2015). Most wearable technologies have features like Wi-Fi, GPRS (General Packet Radio Services), Bluetooth, GPS (Global Positioning System), and third party applications (Costa et al., 2015).
Technology interactions with people / environments / processes
Wearable sensor technology is used for patients in hospitals, elderly in special care and athletes that are trying to track performance. For example, the Apple Watch will monitor someone’s steps and their movements throughout the day. Just because it monitors their movement doesn’t mean that the person will become healthier. Some people use this device to fight obesity (Drury, 2014). These types of devices are used as tools to recognize the user’s or patients abilities and weaknesses (Drury, 2014). Biological wearable technology can be used by anybody that is any age. These types of devices are not subject to one kind of person or skin type. Wearable technology is now making its way to access control points by being able to open doors to businesses (Everett, 2015).
Costs and Benefits
Wearable sensor technology in 2015 was up to $20 billion dollars (Ajami & Teimouri, 2015). The market is expected to rise at least $50 billion dollars in the next ten years (Ajami & Teimouri, 2015). Wearable technology is hard to implement because of the high costs so most small business are not able to aff ...
CINECA webinar slides: Status Update Code of Conduct: Teaming up & Talking ab...CINECAProject
Committed to the drafting of a Code of Conduct for the sector of health research according to Art. 40 GDPR, our initiative is advancing slowly but steadily. Throughout Europe, national jurisdictions differ to a great deal in their interpretations of the GDPR, especially in regard to its application in health research. This is due to some quite vague provisions (public interest, not incompatible clause) as wells as to numerous exemption/derogation clauses concerning the use of health data for research purposes, which encourage States to set up national rules – enhancing fragmentation. Notably, a Code of Conduct can help to bridge the harmonization gaps that may exist between Member States in their application of data protection law. On a practical level, a code is potentially a cost-effective method to achieve greater levels of consistency of protection as well as a mechanism to demonstrate compliance with the GDPR. By spring 2020, several hundred individuals representing around 90 organizations in the field of health research have indicated their interest and support for the Code of Conduct for Health Research. At this stage, this does not yet indicate an endorsement but means that they see a benefit in the development of such a code and are interested in partaking in the process. Additionally, several exchanges take place with national and sectoral codes in order to use synergies and finds ways for collaboration. This webinar is intended to inform you about the latest results.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 1st October 2020 and is part of the CINECA webinar series. It is best viewed in full screen mode using Google Chrome.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
IoT and Mobile Application Based Model for Healthcare Management Systemijtsrd
The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things IoT has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up to date summary of the potential healthcare applications of IoT HIoT based technologies. It is necessary to develop an innovative solution in the Smart Building context that increases guests’ hospitality level during the pandemics in locations like hotels, conference locations, campuses, and hospitals. The solution supports features intending to control the number of occupants by online appointments, smart navigation, and queue management in the building through mobile phones and navigation to the desired location by highlighting interests and facilities. Moreover, checking the space occupancy, and automatic adjustment of the environmental features are the abilities that can be added to the proposed design in the future development. The proposed solution can address all mentioned issues regarding the smart building by integrating and utilizing various data sources collected by the internet of things IoT sensors. Then, storing and processing collected data in servers and finally sending the desired information to the end users. Consequently, through the integration of multiple IoT technologies, a unique platform with minimal hardware usage and maximum adaptability for smart management of general and healthcare services in hospital buildings will be created. Dr. Rajendra Kumar Bharti "IoT and Mobile Application Based Model for Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd51889.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/51889/iot-and-mobile-application-based-model-for-healthcare-management-system/dr-rajendra-kumar-bharti
PharmaLedger Official Presentation OverviewPharmaLedger
Download the Official PharmaLedger Project presentation, which introduces the project, its organisation and summarises the use cases.
In this downloadable presentation, you can find:
An introduction to the PharmaLedger project
PharmaLedger consortium
PharmaLedger objectives
Project organisation and governance
PharmaLedger platform overview
PharmaLedger selected use cases
Project roadmap
Value chain of use cases
Clinical Supply Chain Traceability use case summary
Supply Chain – Finished Goods Traceability use case summary
Supply Chain – E-Leaflet | EPI use case summary
Supply Chain – Anti-Counterfeiting use case summary
Clinical Trial – E-Consent use case summary
Healthdata – Medical Device IoT use case summary
Clinical Trial – Recruitment use case summary
Healthdata – Personalised Medicine use case summary
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This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 853992. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
Disclaimer: Any information on this presentation solely reflects the author’s view and neither IMI nor the European Union or EFPIA are responsible for any use that may be made of the information contained herein.
The document discusses that artificial intelligence will drive the fourth industrial revolution and transform many jobs and industries over the next decade. It provides examples of generative AI technologies that can actively generate results for users in areas like image creation, music generation, and video production. The document also discusses challenges that may arise from increased use of AI, like job losses, and how companies can make decisions using internal corporate data and AI.
AI, IoMT and Blockchain in Healthcare.pdfrectified
This document discusses the application of artificial intelligence, internet of medical things, and blockchain technology in healthcare. Specifically, it covers:
1) How AI, IoMT, and blockchain can enhance patient outcomes, reduce costs, and improve efficiencies in healthcare.
2) Examples of current applications of these technologies, including in breast cancer diagnosis, PCOS diagnosis, and dementia detection. Machine learning algorithms are shown to outperform humans in some medical image analysis and diagnosis tasks.
3) Challenges and future research areas around implementing these technologies, such as ensuring patient privacy and data security.
AI in healthcare has several strengths like telemedicine, drug discovery, and personalized medicine. However, it also faces weaknesses such as data privacy issues and slow learning. Opportunities include reduced costs, 24/7 availability, and faster data analysis. Threats involve bias, job losses, and regulatory hurdles. Ethical challenges pertain to accuracy, overestimating benefits, and unjustified expenses. Considerations around context appropriateness, infrastructure requirements, and avoidance of harms like stigmatization are also important.
FEDERAL LEARNING BASED SOLUTIONS FOR PRIVACY AND ANONYMITY IN INTERNET OF MED...IRJET Journal
This document discusses the use of federated learning (FL) for privacy-preserving analysis of medical data from internet of things (IoT) devices. FL allows decentralized training of machine learning models on devices without moving sensitive patient data to a central location. The rise of IoT in healthcare is generating huge volumes of data but current AI approaches require aggregating data, raising privacy and security concerns. FL emerges as a solution by enabling decentralized and collaborative training while keeping data on devices. The document reviews literature on applying FL to clinical IoT applications and discusses how FL can address data isolation issues and perform AI tasks without compromising privacy.
The document is a code of practice for consumer IoT security that provides 13 guidelines for securing internet-connected devices and associated services. The guidelines address issues such as using unique passwords instead of defaults, keeping software updated, securely storing credentials, encrypting communications, and making it easy for consumers to delete personal data. The aim is to support all parties in developing secure consumer IoT products and services.
Enablers for IoT regarding Wearable Medical Devices to Support Healthy Living...Dr. Mustafa Değerli
This document discusses enablers for the Internet of Things (IoT) regarding wearable medical devices to support healthy living. It conducted a study using a questionnaire distributed to 511 wearable medical device users. Through exploratory factor analysis, it identified five key enablers with 17 total items: 1) Dependability, 2) Design, 3) Worthiness, 4) Privacy, confidentiality and security, and 5) Compatibility. The study provides a checklist for stakeholders to evaluate devices and identify areas for improvement to increase success and adoption of IoT-enabled wearable medical technologies.
IRJET- A Comprehensive Survey on Smart Healthcare Monitoring of Patients usin...IRJET Journal
This document summarizes a research paper that conducted a comprehensive survey on using the Internet of Things (IoT) for smart healthcare monitoring of patients. The key aspects covered are:
1) IoT enables remote patient monitoring through wearable devices that allow healthcare professionals to monitor patients' conditions without being physically present.
2) The survey reviewed various existing works on IoT-based remote patient monitoring systems that transmit patients' health data like temperature and oxygen levels to doctors via wireless networks and mobile apps.
3) Ensuring patient privacy and security while monitoring and accessing health data remotely is an important challenge addressed in some of the existing research.
VeriTeQ provides proprietary healthcare solutions including implantable radio frequency microchip technology cleared by the FDA. The document discusses VeriTeQ's unique value in enabling compliance with an FDA Final Rule requiring medical devices to carry a direct part marking through automatic identification and data capture technology. It also summarizes VeriTeQ's product portfolio in medical device identification, bio-sensing technologies, target markets, and financial projections showing significant revenue growth potential over the next five years.
This document provides an overview of consumer healthtech and discusses the personal information it collects and processes. It notes that consumer healthtech includes wearable devices and apps that track health metrics. It states these technologies collect sensitive data like heart rate, sleep quality, and potentially biomarkers from tears or sweat. The document discusses how this data is initially collected locally by devices but then sent to cloud servers for further processing using AI. It notes potential privacy risks if this health data is leaked, used for unsuitable purposes, or to make inappropriate health decisions about individuals.
Similar to Certifying artificial intelligence-2.pdf (20)
APIs, data formats and the growing might of FHIRVlad Stirbu
This document discusses the evolution of data exchange standards in healthcare over time, from early messaging formats like HL7 to current standards like FHIR and DICOM. It notes the rise of consumer wearables and cloud computing. FHIR is presented as the current gold standard for exchanging healthcare data via APIs. The document cautions that when building healthcare software, one must pay attention to regulations from bodies like the FDA and considerations around intended use, operations in the cloud, and following quality processes.
This is a talk at Health Engineering Finland meetup covering the challenges of using modern agile methodologies for developing medical software. The answer is to how to incorporate activities required by regulations into the #devops activities.
Bringing the software architecture back into agileVlad Stirbu
Modern agile teams are delivering features at ever increasing speed. Automated tests, automatically generated documentation, or continuous integration and delivery make the whole thing look arcane. Only the chosen few can make sense of what is going on.
In this talk we'll have a look at a lean way to document software architecture and how this can be used beyond the development team to support compliance activities.
The document discusses regulatory compliance challenges for medical software development and proposes an automated solution called CompliancePal. CompliancePal would help software developers maintain compliance as they work agilely while providing compliance officers with tools to manage regulations. It would capture architectural decisions and documentation at a fixed level of detail, integrate with development workflows, and generate reports on demand to streamline compliance processes. The goal is to allow medical software teams to "move as agile, act as regulated."
Delivering Features at High Velocity in Regulation Intensive EnvironmentsVlad Stirbu
We use modern development practices to document the code and the APIs exposed by our microservices. We use tools to automatically generate developer portals. Is this enough when developing software used in a regulated domain?
This talk introduces the audience to the particularities of developing medical device software and the regulatory landscape that you must comply with. I’ll focus on the processes and culture that facilitate compliance, without damaging the team velocity and spirit.
This talk introduces the audience to the particularities of developing medical device software and the regulatory landscape that you must comply with. I’ll focus specifically on the processes and culture that enables the creation of medical software device documentation intended for auditors, without damaging (too much) the team velocity and spirit.
A picture is worth a thousand lines of codeVlad Stirbu
The Unified Modeling Language (UML) is a general-purpose, developmental, modeling language in the field of software engineering, that is intended to provide a standard way to visualize the design of a system.
Extending Visual Studio Code allows live UML visualisation of code containing finite state machines.
Patient Care is a new health solution offered by Nokia that enables remote monitoring of patients. Biomedical signals collected via smart devices are analysed in the cloud and the results are presented to medical professionals.
The session will present our methodology of developing microservices that make the Patient Care backend. We pay special attention on testing during the various phases of the development process, and ending with deployment to production, aiming at ensuring that resulting software is compliant with relevant medical software regulations and standards, such as HIPAA or FHIR respectively.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
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.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.