Workshop on Large Language Models and Generative AI for Health at AAAI 2025

Date: March 4th 2025, AAAI 2025, Philadelphia, PA, USA

Registration link: https://aaai.org/conference/aaai/aaai-25/registration/


The rapid evolution of Generative AI, Large Language Models (LLMs), and multimodal models is reshaping the landscape of healthcare. These advanced AI models, when integrated with diverse data types such as clinical notes, medical images, and electronic health records (EHRs), hold immense potential to revolutionize diagnostics, treatment planning, and patient management. This workshop will bring together experts to explore the transformative role of AI in healthcare while addressing the critical challenges that come with it.

Despite their promise, the adoption of LLMs and Generative AI in healthcare is not without obstacles. Issues around fairness, trust, clinical validation, and bias mitigation are central to this discussion. How can we ensure that these models are transparent, ethical, and comply with regulatory standards? What strategies can mitigate inherent biases and build trust with both clinicians and patients?

This workshop will foster interdisciplinary collaboration between AI researchers, healthcare professionals, and policymakers. It aims to bridge the gap between cutting-edge technological innovations and real-world clinical practice, ensuring that AI-driven healthcare is effective, trustworthy, and accessible to all patients.

Topics of Interest

We invite high-quality submissions in (but not limited to) the following areas:

Large Language Models (LLMs) for Clinical Data: Natural language processing of medical notes, EHRs, and patient narratives using LLMs.

Generative AI in Medical Imaging: Applications of generative models for interpreting and enhancing medical images (e.g., X-rays, MRI, CT scans).

Multimodal AI for Healthcare: Combining text, image, and structured data for comprehensive patient assessments and decision support.

Clinical Decision Support Systems (CDSS): AI-based systems that assist healthcare providers in diagnosis and treatment planning.

Ethics and Fairness in AI: Methods for addressing bias, fairness, and explainability in AI models in clinical settings.

Trust and Transparency: Building trustworthy AI systems that clinicians and patients can rely on for accurate diagnosis and care.

Regulatory Compliance and Standards: Challenges and solutions in ensuring that AI models comply with healthcare regulations and ethical standards.

Real-World Applications: Case studies and implementations of LLMs and generative AI in real-world healthcare settings.

AI for Public Health: Applications of AI in large-scale health monitoring, disease outbreak prediction, and population health management.

Interdisciplinary Collaboration: Best practices for fostering collaboration between AI researchers, healthcare providers, and policy makers.

Submission Guidelines

We invite original research papers, position papers, and case studies. Submissions should align with the workshop’s focus on advancing AI in healthcare while addressing ethical, technical, and clinical challenges.

Paper Length: Submissions should be up to 6 pages (excluding references), following the AAAI 2025 paper format.

Submission Link: https://openreview.net/group?id=AAAI.org/2025/Workshop/GenAI4Health


Important Dates

Submission Deadline: Friday, November 22nd, 2024  extended to: Friday, November 29th, 2024

Notification of Acceptance: Monday, December 9th, 2024

Camera-Ready Submission: TBD

Workshop Date: AAAI 2025 (Exact Date: March 4th, 2024)


For any questions or further details, please contact us at d.chaudhary@northeastern.edu

We look forward to your contributions and to an engaging discussion on the future of AI in healthcare!

Invited Speakers

Keynote

Heng Huang

University of Maryland

Su-In Lee

University of Washington

Jiebo Luo

University of Rochester

Jimeng Sun

University of Illinois Urbana-Champaign

Milind Tambe

Harvard University

Aidong Zhang

University of Virginia

Chenyan Xiong

Carnegie Mellon University

Panel

TBD


Talk

TBD


Core Organizers

Kaidi Xu

Drexel University

Pengtao Xie

University of California San Diego

Divya Chaudhary

Northeastern University

Organizing Board

Monica Agrawal

Duke University

Ying Ding

University of Texas at Austin

Bethany Edmunds

Northeastern University

Judy Gichoya

Emory University

Halil Kilicoglu

University of Illinois

Rahul Krishnan

University of Toronto 

Qi Long

University of Pennsylvania

Pranav Rajpurkar

Harvard University

Justin Rousseau

UTexas Southwestern Medical Center

Rajiv Ratn Shah

IIIT-Delhi

Li Shen

University of Pennsylvania

Jon Tamir

University of Texas at Austin

Sahil Wadhwa

Capital One

Huanmei Wu

Temple University

Eric Xing

Mohamed bin Zayed University of Artificial Intelligence,

Carnegie Mellon University

GQ Zhang

UT Health

Student Chair

Jinhao Duan 

Drexel University

Peng Zhang

Northeastern University