Overview

Healthcare today stands at the intersection of technology and innovation, driven by diverse data sources—from clinical reports and electronic health records to medical imaging, vital signs, and numerous forms of unstructured data. While deep learning has significantly advanced medical imaging, the vast potential of integrating these abundant, multi-modal data streams remains largely untapped. This integration promises revolutionary improvements in patient outcomes, yet navigating this landscape poses unique and complex challenges due to the fragmented and isolated nature of healthcare data. This workshop addresses the critical questions facing researchers and practitioners: How can we effectively align and integrate multi-modal medical data? How do we tackle safety, privacy, interpretability, and the scarcity of clinically driven benchmarks?

Join us to explore cutting-edge research, engage with leading experts in the field, and discover exciting opportunities to leverage multi-modal models to drive the next generation of healthcare innovations. Be part of the conversation shaping the future of medicine.

Speakers

Lena-Maier
            Hein

Lena-Maier Hein

German Cancer Research Center | National Center for Tumor Diseases, Heidelberg

Akshay Chaudhari

Akshay Chaudhari

Stanford

Tim Deyer

Tim Deyer

Weill Cornell Medicine | New York Hospital | East River Medical Imaging

Daniel Rueckert

Daniel Rueckert

TU Munich | Imperial College London

Michael Moor

Michael Moor

ETH Zurich

Workshop Schedule

Organizers

Vishwesh Nath

Vishwesh Nath

NVIDIA

Jeya Maria Jose V.

Jeya Maria Jose V.

Microsoft Research

Zhihong Chen

Zhihong Chen

Stanford

Catie Chang

Catie Chang

Vanderbilt

Xueyan Mei

Xueyan Mei

Mount Sinai

Weidi Xie

Weidi Xie

SJTU

Vishal Patel

Vishal Patel

Johns Hopkins

Bennett Landman

Bennett Landman

Vanderbilt

If you have any questions, please feel free to reach out to mandm.academic.workshop@gmail.com.