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What challenges are presented by AI adoption in healthcare? What role should AI governance play in regard to the opportunities and risks for generative AI (large language models like ChatGPT-4, etc.) in health? How do we responsibly evaluate new technology and ensure guardrails for its deployment, but without stifling innovation? How do we address societal fears and biases? What level of reliability and robustness should algorithms achieve before being adopted with confidence across healthcare? How can AI support health equity and expand access? We will explore these questions and more with some of the nation’s leading experts on these topics.
Generative AI application examples
Synthesis and Summarization of Medical Research
Calvin Lawrence, Distinguished Engineer – Responsible AI , Member of AI Ethics Board and Academy of Technology, IBM
Seth Dobrin, PhD, Founder and CEO, Qantm AI
Gil Alterovitz, PhD, Director, Biomedical Cybernetics Laboratory Harvard Medical School, Member of CHAI
Yoav Schlesinger Architect, Ethical AI Practice, Healthcare Salesforce
Dennis Chornenky, Chief AI Advisor UC Davis Health and CEO, Domelabs AI, Moderator
This panel will explore the exciting potential of telehealth for women’s health, and how innovation is transforming the field. Join industry leaders discuss the future of women’s telehealth and innovative solutions that are unlocking better care for women, including how patients connect with providers for virtual consultations, receive prescriptions, order birth control, and access at-home STI testing.
• Learn how telehealth is used to improve access to women’s health services, including OB/GYN care and family planning in a hybrid environment using an integrated platform
• Learn how telehealth provides personalized care to women through a comprehensive, holistic approach that addresses physical and mental health
• Explore telehealth support for new mothers with breastfeeding, including virtual lactation consultations and personalized care plans
Bronwyn Harris, CEO, Carbon Health
Andrea Ippolito, CEO, and Founder SimpliFed
Aditi Joshi, Founder, Nagamed Digital Consulting
Matt Sakumoto, Professor, USCF, Moderator
How can community health professionals connect with resident health consumers to encourage positive self care? This goes beyond encouraging physical activity to encompass a range of life style behavior changes with a tailored approach that engages those least engaged with health and wellness and potentially most at risk from acute health risks and longer term conditions such as Type 2 Diabetes. Is the answer purely digital, or does a network of health service managers help drive engagement and better outcomes? This session explores how a data driven, dynamically adaptive approach and adding an “administrator portal” shapes targeted incentives and messaging, adjusting parameters of rewards and behavioral triggers for personalized content. The speaker will present a case use from Hounslow and Buckinghamshire in the UK, where healthcare is optimized through self learning systems.
• Insight into own practices and the balance between acute and preventative care
• Understand how smartphone technology, combined with incentives, can be used to engage community residents in their own self care
• Learn how to baseline existing behavior and measure change over time
• Gain insights from smartphone derived data and understand how it can be used to identify barriers to change
Hannah McCarthy, COO, BetterPoints Ltd
Case Use 1:
How data is stored, shared and monetized connecting an entire ecosystem with benefits.
Case Use 2:
EHRs, genomic DNA, wearables, pharmacy and social determinants of health data and accelerated access to de-identified, tokenized, real-time data.
Dr. Igor Korolev, Digital Health Consultant
Stephan Manoryk Community Leader DeHealth
Ardy Arianpour, CEO, Seqster CEO
Jim St. Claire, COO & Advisor, Multiple Companies, Moderator
In our rapidly advancing technological landscape, artificial intelligence (AI) has emerged as a powerful tool with the potential to revolutionize healthcare, telehealth, and medicine. However, alongside its immense potential come critical ethical considerations that must be addressed. Delve into the ethical dimensions of AI in these domains and the complex challenges and dilemmas that arise through real-world case studies highlighting the
ethical implications of AI in healthcare delivery, telehealth services, and medical decision-making, ethical challenges of using AI algorithms in diagnosing diseases, determining treatment plans, patient privacy and informed consent, and the socioeconomic impact of AI in healthcare, such as job displacement, access to care, and disparities in health outcomes.
Further, panelists will examine existing ethical frameworks and explore the challenges of integrating AI into existing healthcare systems while maintaining human-centered care and preserving the doctor-patient relationship.
Asha Saxena, Founder and CEO, Women Leaders In Data & AI (WLDA)
Dr. Keng-Yen Huang, Associate Prof, Population Health & Child and Adolescent Psychiatry, NYU School of Medicine
Cortnie Abercrombie, CEO and Founder, AI Truth
Dr. Besa H. Bauta, Adj. Assistant Professor, New York University
Tune into this dynamic session on Exponential Leaps in Medicine with XR, and discover how XR technologies are revolutionizing healthcare, from surgical simulations to patient care. Explore the regulatory challenges and clinical solutions associated with adopting XR in medicine. Gain insights from the speakers on their experiences and leave inspired by the transformative potential of XR in healthcare.
• Provide an overview of the current state and applications of medical extended reality (XR) technologies in healthcare.
• Discuss the benefits and challenges of the state of XR in medicine.
• Explore the future potential and ethical considerations of medical XR in healthcare.
• Gain insights on how medical XR can be used in current and future healthcare environments.
• Understand regulatory frameworks that could be put in place to ensure consumers and end-users are appropriately protected.
Mark Zhang, DO, MMSc, FAMIA, Associate Chief Medical Information Officer – Digital Innovation Brigham and Women’s Hospital
Dan Scarf, CEO, XRAI Glass
Claude Pirtle, CMIO, Walmart Health, Moderator
How do we evaluate large language models for use in healthcare? What are the trusted frameworks for value assessment? Is automation through GPT successfully addressing the healthcare administrative and workforce crisis? What about clinical decision making? Expect a candid discussion from these experts on the implications of LLM’s and AI in Primary Care in the US and around the globe.
• Acquire knowledge of the fundamental principles of large language models
• Understand how these models are trained and deployed in a healthcare context
• Learn how to assess the efficiency and effectiveness of large language models in healthcare
• Understand the measures used in determining the success of these models, such as improved patient outcomes, efficiency in operations, and patient satisfaction
• Learn to apply evaluation or translational frameworks in assessing the value of large language models
• Gain insights into how automation, specifically through GPT, is helping to solve healthcare administrative challenges
• Learn about the use of large language models in clinical decision-making
• Understand the strengths and limitations of these models in making clinical decisions, administration, and the ethics
Sandeep Reddy,Director, MBA(Healthcare Management), Deakin School of Medicine
and Chairman, Medi-AI
Alexandre Lebrun, CEO, Nabla
Adam Chee, PhD, Chief, Smart Health Leadership Centre, Institute of Systems Science National University of Singapore
Dimitris Kalogeropoulos, CEO, Global Health and Digital Innovation Foundation, Moderator
Governments and technology companies are increasingly collecting vast amounts of personal data, prompting new law, myriad investigations, and calls for stricter regulation to protect individual privacy. Yet despite these issues, economics tells us that society needs and is demanding more data sharing rather than less, because the benefits of publicly available data often outweigh the costs. Better economic data could vastly improve policy responses to the next crisis. Data increasingly powers innovation, and it needs to be used for the public good, while individual privacy is protected. This is new and unfamiliar terrain for policymaking, and it requires a careful approach. The pandemic has brought the increasing dominance of big, data-gobbling tech companies into sharp focus. From online retail to home entertainment, digitally savvy businesses are collecting data and deploying it to anticipate product demand and set prices, lowering costs and outwitting more traditional competitors. This session features three experts who will discuss the challenges of balancing citizen and patient privacy with open data sharing for the public good and improved population health.
• Explore how open data can improved efficiencies and reduced costs
• Learn how increased transparency can increase accountability and lead to less corruption
• Consider how open data has the potential to bring people together who are working on similar
issues who can exchange ideas, findings, discuss challenges, and encourage data collaboration
rather than competitiveness
• Appreciate the hazards and costs for incorrect use of data and missing data
Lorenzo Cristofaro, Partner, Panetta Law
Dr. Paul Barach, Professor, Thomas Jefferson University
Dr. Osama El-Hassan, Health Informatics Specialist, Dubai Health Authority
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