GenAI for Health: Potential, Trust and Policy Compliance

Co-located with NeurIPS 2024

December 14, 2024

East Meeting Room 16, Vancouver Convention Center

Keynote Speakers

James Zou
James Zou

Stanford University

David Sontag
David Sontag

MIT & Layer Health

Zachary Lipton
Zachary Lipton

CMU & Abridge

Sarita Joshi
Sarita Joshi

Google Cloud

Ayo Adedeji
Ayo Adedeji

Google Cloud

Su-In Lee
Su-In Lee

University of Washington, Seattle

Bo Li
Bo Li

University of Chicago & Virtue AI

Yuyin Zhou
Yuyin Zhou

University of California, Santa Cruz

Sanmi Koyejo
Sanmi (Oluwasanmi) Koyejo

Stanford University

Connor T. Jerzak
Connor T. Jerzak

University of Texas at Austin

Snehalkumar 'Neil' Gaikwad
Snehalkumar 'Neil' Gaikwad

University of North Carolina at Chapel Hill

Schedule

TIME EVENT & PRESENTERS
8:15 am - 8:20 am Welcome by the organizers
8:20 am - 8:40 am Keynote: Daguang Xu (NVIDIA)
8:40 am - 9:00 am Keynote: Tanveer Syeda-Mahmood (IBM)
9:00 am - 9:20 am Keynote: James Zou (Stanford)
9:20 am - 9:50 am Coffee Break
9:50 am - 10:10 am Keynote: David Sontag (MIT & Layer Health)
10:10 am - 10:30 am Keynote: Zachary Lipton (CMU & Abridge) Ying Ding (UT Austin)
10:30 am - 10:40 am Oral (Research Track): Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
10:40 am - 10:50 am Oral (Research Track): PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals
10:50 am - 11:00 am Oral (Research Track): Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
11:00 am - 11:10 am Oral (Position Paper): Participatory Assessment of Large Language Model Applications in an Academic Medical Center
11:10 am - 11:30 am Keynote: Sarita Joshi and Ayo Adedeji (Google)
11:30 am - 12:10 pm Panel: Generative AI Health in Industry
Panelists: Daguang Xu, Tanveer Syeda-Mahmood, James Zou, David Sontag, Zachary Lipton, Sarita Joshi and Ayo Adedeji
Moderator: Jason Alan Fries
12:10 pm - 1:00 pm Lunch Break (Poster Session Preparation)
1:00 pm - 1:50 pm Poster Session
1:50 pm - 2:00 pm Invited Talk: Morse & ARCLab (Winner from NeurIPS 2024 LLM Privacy Challenge)
2:00 pm - 2:20 pm Safety Keynote: Bo Li (UChicago & Vritue AI)
2:20 pm - 2:40 pm Safety Keynote: Yuyin Zhou (UCSC)
2:40 pm - 3:00 pm Ethics Keynote: Sanmi Koyejo (Stanford)
3:00 pm - 3:30 pm Policy Keynote: Connor T. Jerzak (UT Austin)
3:30 pm - 3:50 pm Policy Keynote: Snehalkumar 'Neil' Gaikwad (UNC)
3:50 pm - 4:10 pm Keynote: Su-In Lee (UW)
4:10 pm - 4:20 pm Coffee Break
4:20 pm - 4:50 pm Poster session
4:50 pm - 4:55 pm Award Ceremony
4:55 pm - 5:30 pm Panel: Safety, Ethics and Policy for Generative AI in Health
Panelists: Bo Li, Yuyin Zhou, Sanmi Koyejo, Connor T. Jerzak, Snehalkumar 'Neil' Gaikwad, Su-In Lee
Moderator: Ying Ding

Introduction

Generative AI (GenAI) emerged as a strong tool that can revolutionize healthcare and medicine. Yet the public trust in using GenAI for health is not well established due to its potential vulnerabilities and insufficient compliance with health policies. The workshop aims to gather machine learning researchers and healthcare/medicine experts from both academia and industry to explore the transformative potential of GenAI for health. We will delve into the trustworthiness risks and mitigation of cutting-edge GenAI technologies applicable in health applications, such as Large Language Models, and multi-modality large models. By fostering multidisciplinary communication with experts in government policies, this workshop seeks to advance the integration of GenAI in healthcare, ensuring safe, effective, ethical, and policy-compliant deployment to enhance patient outcomes and clinical research.

Call for Submission

Workshop Scope

We invite paper submissions that have not been published, falling in but not limited to the following topics.

Topic 1: GenAI use cases

For example, surveys of GenAI in healthcare, methodologies of using GenAI for data synthesis, simulation (e.g., digital twins), preliminary study, improving diagnosis accuracy, treatment assistance, and digital therapies.

Topic 2: Trustworthiness and risks

For example, novel benchmarks of GenAI safety in specific or general health use cases, potential misuse, safeguarding techniques, reliability, and ethical disparities.

Topic 3: Policy and compliance

For example, reviews of the latest policies in the association of AI and health, evaluation of the compliance of current GenAI applications, and pipelines to coordinate policymakers, GenAI developers, and security experts.

Papers will be submitted in three tracks: demonstration papers for the GenAI health applications, research papers for the policy-compliant GenAI trustworthiness in health or methodology of using GenAI for health, and position papers discussing policies and solutions for technical compliance. We encourage authors to involve multidisciplinary experts, especially the health community (e.g., stakeholders) and policymakers in writing the papers, which ensures the developed methods can address emerging stakeholders' and policymakers' concerns. Accepted papers will be non-archival and presented on the workshop website.

Submission Guidelines

Camera-ready
For the camera-ready version, please compile it with the [final] option. For example:\usepackage[final]{neurips_2024}. Please replace the original neurips_2024.sty file with this one, which has been slightly adapted from the NeurIPS 2024 style for use in the workshop's camera-ready submission.
Submission Tracks
(1) Demo Track: Papers demonstrating critical use cases of AI in health. (2) Position Track: Papers presenting new challenges/trends in safety or policy compliance in the area of GenAI for health. A more detailed definition may refer to the ICML 2024 call for position paper The paper title should include "Position:". (3) Research Track: Papers that present novel methodologies or insights addressing critical challenges in GenAI for healthcare or related safety and policy.
Submission Format
You must format your submission using the NeurIPS 2024 LaTeX style file. Use `\usepackage{neurips_2024}` without options to ensure the submission is anonymous. Submissions that violate the NeurIPS style (e.g., by decreasing margins or font sizes) or page limits may be rejected without further review. Papers may be rejected without consideration of their merits if they fail to meet the submission requirements, as described in this document. All page limit excludes references and appendix. (1) Demo Track: The paper title should include "Demo:". No longer than 5 pages. (2) Position Track: The paper title should include "Position:". No longer than 5 pages. (3) Research Track: No longer than 9 pages.
Submission Link
Papers should be submitted at the Openreview Website
Review Process
All papers will be double-blinded and peer-reviewed by at least 3 reviewers. All submissions must be anonymized and may not contain any identifying information that may violate the double-blind reviewing policy. This policy applies to any supplementary or linked material as well, including code. If you are including links to any external material, it is your responsibility to guarantee anonymous browsing. Please do not include acknowledgements at submission time. If you need to cite one of your own papers, you should do so with adequate anonymization to preserve double-blind reviewing. For instance, write "In the previous work of Smith et al. [1]…" rather than "In our previous work [1]..."). If you need to cite one of your own papers that is in submission to NeurIPS and not available as a non-anonymous preprint, then include a copy of the cited anonymized submission in the supplementary material and write "Anonymous et al. [1] concurrently show..."). Any papers found to be violating this policy will be rejected.
Presentation
All accepted papers will be presented with posters. High-quality papers will also have the opportunity for oral/spotlight presentations and win Best Paper Award(s) per track. All accepted papers are expected to be presented in person.

The accepted papers will be non-archival (NOT included in proceedings or any form of publication).
Awards
The organizing committee will select best paper award(s).

Important Dates

Submission Site Open July 25, 2024
Paper Submissions August 30 September 10, 2024, AoE
Paper Notifications October 11, 2024, AoE
Camera-ready Submission November 11, 2024, AoE
Last Chance for Registration Refund November 15, 2024, 11:00 PM PST
Workshop date December 14, 2024

Sponsors

sponsor
sponsor

Organizers

Organizer 1
Junyuan Hong

University of Texas at Austin

Organizer 2
Pranav Rajpurkar

Harvard University

Organizer 3
Jason Alan Fries

Stanford University

Organizer 4
Marina Sirota

University of California, San Francisco

Organizer 5
Ying Ding

University of Texas at Austin

Local Chair

Sheng Liu
Sheng Liu
[Primary local contact]

shengl@stanford.edu

Stanford University

Program Award Committee

Atlas Wang
Atlas Wang

University of Texas at Austin

Sheng Liu
Sheng Liu

Stanford University

Student Organizers

Organizer 6
Jiawei Xu

University of Texas at Austin

Volunteer Organizer for Local Events

Contact: jiaweixu@utexas.edu

Organizer 6
Junjie Tang

University of Texas at Austin

Volunteer Organizer for Web

Program Committee

  • Canyu Chen (Illinois Institute of Technology)
  • DeBrae Kennedy-Mayo (Georgia Institute of Technology)
  • Connor Thomas Jerzak (University of Texas at Austin)
  • Gregory Holste (University of Texas at Austin)
  • Jinhao Duan (Drexel University)
  • Iain Nash (Edge Hill University)
  • Liangyu Chen (Computer Science Department, Stanford University)
  • Wenlong Deng (University of British Columbia)
  • Qinbin Li (University of California, Berkeley)
  • Zepeng Frazier Huo (Stanford University)
  • Brandon Philip Theodorou (University of Illinois at Urbana-Champaign)
  • Yixiong Chen (Johns Hopkins University)
  • Xingbo Fu (University of Virginia, Charlottesville)
  • Tianhao Li (University of Texas at Austin)
  • Joseph Paul Cohen (Amazon)
  • Thesath Nanayakkara (University of Pittsburgh)
  • Ajay Kumar Jaiswal (Apple)
  • Md Mahfuzur Rahman (Georgia State University)
  • Monica Munnangi (Northeastern University)
  • Mira Moukheiber (Massachusetts Institute of Technology)
  • Shantanu Ghosh (Boston University)
  • Yu-Cheng Chou (Johns Hopkins University)
  • Song Wang (University of Texas at Austin)
  • Xiaoman Zhang (Harvard Medical School, Harvard University)
  • Shuhao Fu (University of California, Los Angeles)
  • Yixin Wang (Stanford University)
  • Wenqi Shi (University of Texas Southwestern Medical Center)
  • Guangzhi Xiong (University of Virginia, Charlottesville)
  • Meirui Jiang (Department of Computer Science and Engineering, The Chinese University of Hong Kong)
  • Xingbo Wang (Weill Cornell Medical College, Cornell University)
  • Maryam Khalid (Rice University)
  • Ziyi Huang (Columbia University)
  • Prithwish Chakraborty (Amazon)
  • Zhixin Lai (Snap Inc.)
  • Ran Xu (Emory University)
  • Yasunobu Nohara (Kumamoto University)
  • Syed Hasan Amin Mahmood (Purdue University)
  • Zhenglun Kong (Harvard Medical School, Harvard University)
  • Zhe Huang (Tufts University)
  • Weicheng Zhu (New York University)
  • Xinyu Zhao (University of North Carolina at Chapel Hill)
  • Zijie Liu (Washington University, Saint Louis)
  • Qixin Hu (Huazhong University of Science and Technology)
  • Jing Ma (Case Western Reserve University)
  • Liu Chen (Massachusetts General Hospital, Harvard University)
  • Martin Norgaard (University of Copenhagen)
  • Ruishan Liu (University of Southern California)
  • Juan Helen Zhou (National University of Singapore)
  • Kaiwen Zha (Massachusetts Institute of Technology)
  • Han Xie (Emory University)
  • Shiru Wang (Dartmouth College)
  • Yushun Dong (Florida State University)
  • Siyu He (Stanford University)
  • Mahed Abroshan (Imperial College London)
  • GUOJUN XIONG (School of Engineering and Applied Sciences, Harvard University)
  • Haoyang Li (Cornell University)
  • Haipeng Chen (College of William and Mary)
  • Shuang Li (The Chinese University of Hong Kong (Shenzhen))
  • Haobo Zhang (Michigan State University)
  • Kaidi Xu (Drexel University)
  • Chulin Xie (University of Illinois, Urbana Champaign)
  • Zixin Ding (University of Chicago)
  • Zhangheng LI (University of Texas at Austin)
  • Shrey Pandit (University of Texas at Austin)
  • Haoyang Wang (University of Texas at Austin)
  • Sidharth Kumar (University of Texas at Austin)
  • Chaojian Li (Georgia Institute of Technology)
  • Alexander Rasgon (University of Texas at Austin)
  • SayedMorteza Malaekeh (University of Texas at Austin)
  • Xinye Wang (Georgia Institute of Technology)