Workshop Agenda

TLDR: Join us for an exciting day-long session about how the landscape of clinical care is changing in response to AI. Building on the longstanding MLHC tradition of hosting a workshop prior to the main conference, this event brings together students, healthcare providers, machine learning researchers, and industry leaders, for a hands-on, discussion-driven program. No prior experience with machine learning is required.

AI is rapidly reshaping healthcare by transforming how clinicians interpret evidence, make decisions, and engage with clinical data. This workshop examines the evolving role of healthcare professionals and researchers across three domains: evaluating AI research, integrating AI into clinical workflows, and leveraging open-source AI tools for medical imaging.

The American Medical Association will kick off the workshop by surveying the current sentiment of AI in healthcare and how medical education and training can be augmented with the use of AI. We will then discuss how to critically evaluate claims about the performance of AI systems, clarifying what constitutes meaningful evidence for safe and effective adoption.

Attendees will then learn from Claude Health about the evolving role of large language models in healthcare and research and will then navigate real-world clinical scenarios using these models. By stress-testing leading models like Google’s Gemini, OpenAI’s ChatGPT, and Anthropic’s Claude, participants will gain a better understanding of where these tools excel and where their limitations lie.

Participants will then explore how AI models can extract clinically relevant information from medical images, using open-source tools in a session led by NVIDIA. Across themes, this highly interactive workshop centers participants as evaluators, supervisors, and partners in responsible uses of AI in healthcare.

Who Should Attend

This workshop is designed for:

Anyone with curiosity about how AI is transforming healthcare
Healthcare providers interested in understanding and shaping AI-enabled care
Machine learning researchers studying problems facing current clinical AI
Industry practitioners building or deploying clinical AI tools
Regulators and policy-adjacent researchers
Students/trainees seeking practical frameworks for evaluating clinical AI

What to Expect

🏛️ Perspectives from the American Medical Association (9-10AM)

Invited speakers will discuss:

Physician enthusiasm and concern about AI in healthcare
Modernizing medical education with AI
Principles to guide the responsible development and deployment and use of AI

🔍 How to Read and Review a Clinical AI Paper (10AM-12PM)

Case-study driven session on how to critically read and evaluate research in the rapidly evolving landscape of AI in healthcare, with a focus on clinical relevance, safety, and validity. Clinicians will gain familiarity with computational methodology while non-clinicians will learn to assess clinical impact and validity.

🥪 Lunch (12-1PM)

🗨️Perspectives from Claude Health (1-1:45PM)

A session led by the Claude Health team, introducing participants to the evolving role of large language models in clinical care and research.

🩺 Interactive Clinical Scenarios (2-3PM)

Case-based discussions exploring how large language models intersect with real clinical workflows. Participants will reason through benefits, risks, and unintended consequences, grounded in realistic clinical contexts including:

Diagnosis and treatment planning
Supporting patient counseling
Clinical note-writing and documentation

🖼️ Hands-On Session: Generative AI for Medical Imaging (NVIDIA) (3-4PM)

A practical session led by NVIDIA, showcasing tools and workflows for applying open-source tools to medical images.