Generative AI for Healthcare Agenda

Registration, Breakfast and Networking

Chair’s Opening Remarks & Setting the Scene

Unlocking the Fundamentals of Generative AI for Healthcare

Keynote Presentation: How Do We Demystify Generative AI for Healthcare?

• Defining generative AI for healthcare and its use cases,
• A deep dive into the regulatory and ethical issues facing the adoption of generative AI in healthcare,
• An overview of how physicians and patients will harness generative AI looking to the future, and how this will improve population health outcomes.

Shafiq Rab, Chief Digital Officer, System Chief Information Officer and Executive Vice President, Tufts Medicine

Keynote Panel with Open Q&A: Generative AI and Healthcare: Are They Ready For Each Other?

In this keynote panel discussion, panelists will explore the uses of generative AI in healthcare, its safety, and the promise it holds to shape the future of the healthcare industry and benefit population health outcomes… 

• Does generative AI have a place in the future of healthcare and what will this look like? 
• Where do the different stakeholder groups on this panel see the biggest impact of generative AI in their industry?
• Where are the opportunities for generative AI to revolutionize the patient experience?
• Are partnerships essential to scaling generative AI across healthcare, and what are the current partnerships driving innovation?
• Is Generative AI ready to safely deliver better health outcomes in health systems, and ensure a return on investment?

Divya Pathak, Vice Chair – Artificial Intelligence – Center for Digital Health – Mayo Clinic
Yanshan Wang, PhD, FAMIA, Vice Chair of Research and Assistant Professor, University of Pittsburgh
Sandy Aronson, ALM, MA. Executive Director of Information Technology, Mass General Brigham Personalized Medicine
Jeffery Smith, Deputy Director, Certification & Testing Division, Office of the National Coordinator for Health Information Technology (ONC)

Morning Refreshments & Networking

Revolutionizing Workflows in Healthcare With Generative AI

Case Study: Opportunities to Automate the Prior Authorization Process

Speaker: To Be Announced…

Panel with Open Q&A: Could Generative AI be the Answer to Healthcare’s Biggest Challenges?

This panel discussion addresses the ways in which generative AI could alleviate some of the key challenges facing the healthcare industry, while exploring how we can get there looking forward…

• What’s the promise of generative AI in reducing healthcare disparities?
• What are the main hurdles and opportunities associated with using generative AI to remedy health inequities?
• How could AI methods be used to overcome key workforce challenges facing healthcare, for example: burnout and the increased numbers of those leaving healthcare professions?
• What are some potential adverse effects on the healthcare workforce associated with the integration of generative into healthcare? 
• How can we equip healthcare workers with the tools to facilitate adoption of generative AI into healthcare?

Mike Harmer, Vice President of Workforce Intelligence and Talent, Intermountain Healthcare
William Gordon, MD, MBI, FAMIA, Senior Advisor of Data and Technology, Center for Medicare and Medicaid Innovation
Francis Suo, Associate Vice President of Data Science, CVS Health (Aetna)

Lunch

Data, Ethics and Governance

Case Study: Revolutionizing Healthcare with Synthetic Data

Billy Oglesby, Dean, Jefferson College of Population Health, Thomas Jefferson University

Case Study: Leveraging Generative AI to Accelerate Precision Medicine

Shameer Khader, Executive Director, Global Head of Data Science, Data Engineering and Computational Biology, Sanofi

Afternoon Refreshments & Networking

Panel with Open Q&A: Navigating the Data and Ethical Hurdles Surrounding Generative AI

As the healthcare industry continues to navigate the adoption of generative AI technologies into healthcare workflows, unprecedented, yet crucial, discussion surrounding: liability for model outputs, data privacy and regulation arise. This panel discussion will delve into these topics and explore how we can ensure the ethical integration of generative AI into healthcare while prioritizing patient interests.

• Where are the main data bottlenecks in the integration of generative AI in healthcare systems today?
• How essential will training data be to increase trust and credibility in generative AI models, and what are the techniques to overcome bias?
• What current regulatory framework is in place to support the adoption of generative AI into health systems, and who is the governing body?
• Who will accept liability and responsibility for the outputs of generative AI models in healthcare, and who is at fault if something is incorrect?
• How will we be able to ensure patient’s data privacy and autonomy over how their data is used, while experiencing the benefits that could come with generative AI e.g. personalized medicine?

Shahidul Mannan, Chief Data Officer, Bon Secours Mercy Health
Girish Nadkarni, Chief, Division of Data Driven and Digital Medicine (D3M), Mount Sinai Health System
Amy Booth, Director of Analytics, United Health Services
Sumeet Chugh, Director, Division of Artificial Intelligence in Medicine, Cedars Sinai Health System

Chair’s Closing Remarks

End of the Generative AI for Healthcare Summit Day 1

Registration, Breakfast & Networking

Chair’s Opening Remarks

Opportunities and Future Vision

Keynote Presentation: Generative AI and Healthcare: Purpose and Promise

• A deep dive into what generative AI is and what this means for healthcare,
• Identifying the purpose and promise of generative AI in healthcare,
• A look into the current advancements within generative AI for healthcare this year.

Aalpen Patel, Medical Director for Artificial Intelligence, Geisinger and Steele Institute for Health Innovation

Case Study: Generative AI: A Paradigm Shift in Biomedical and Clinical Natural Language Processing

The utilization of natural language processing (NLP) technology has become increasingly important in the biomedical and clinical fields, as much of the valuable information is embedded within narratives found in biomedical literature and electronic health records (EHRs). From rule-based algorithms to advanced deep learning neural networks, various techniques have been employed in biomedical and clinical NLP systems. The advent of large language models (LLMs) and generative artificial intelligence (AI), such as ChatGPT, has generated a great deal of interest in the NLP field. LLMs have revolutionized biomedical and clinical NLP tasks, providing a new paradigm for these tasks by using zero/few-shot learning approaches. However, while these models have shown promise, they also have limitations for direct healthcare applications. This presentation will explore the traditional biomedical and clinical NLP techniques that have been successful in the medical domain, as well as the potential of generative AI and recent research outcomes from Dr. Wang’s team for biomedical and clinical NLP.

Yanshan Wang, PhD, FAMIA, Vice Chair of Research and Assistant Professor, University of Pittsburgh

Morning Refreshments & Networking

Case Study: Optimizing Healthcare for an Ageing Demographic

• A look into how United Health Services are leveraging generative AI to address the needs of aging populations,
• Identifying the current success stories of utilizing generative AI to optimize patient care and better meet patients needs.

Amy Booth, Director of Analytics, United Health Services

Case Study: Generative AI and the Future of Primary Care

Steven Lin, Executive Director – Stanford Healthcare AI Applied Research Team, Stanford University

Panel with Open Q&A: Future Opportunities: Generative AI in Healthcare

In this concluding panel, speakers explore the future of generative AI in healthcare, and how to navigate the challenges associated with implementing these new technologies, while adapting current healthcare models to facilitate this. There is also opportunity for attendees to have their say, through an open Q&A to the panelists…

• What will the future of healthcare look like, and will this change current healthcare models?
• Will generative AI alone solve the current issues facing healthcare, for example: access, health equity, affordability, poorer health outcomes and fragmentation?
• Are we being realistic with what generative AI can and can’t do for healthcare?
• How will we pay for Generative AI in Healthcare and will this be part of the value-based care strategy? 
• Where is the cutting-edge innovation taking place within generative AI for healthcare that interests investors?

Katherine Gergen Barnett, MD. Vice Chair of Primary Care Innovation and Transformation, Boston Medical Center
Steven Lin, Executive Director – Stanford Healthcare AI Applied Research Team, Stanford University
Jason J. Parent, MSN, APRN, FNP-C. Director of Clinical Innovation, Point32Health

Chair’s Closing Remarks

End of the Generative AI for Healthcare Summit