The special session on Foundation Models in Medicine (FMM) is part of the International Joint Conference on Neural Networks (IJCNN 2025), which will be held at the Pontifical Gregorian University, Rome, Italy, from Monday, June 30th to Saturday, July 5th, 2025.

Foundation Models (FMs) mark a breakthrough in deep learning, distinguished by their large-scale and task-agnostic design. Trained through self-supervised learning on vast and diverse datasets, these models acquire a broad understanding that can be applied to a range of downstream tasks. 

In the medical field, FMs hold transformative potential, from clinical natural language processing and advanced computer vision for medical imaging analysis to multimodal data integration supporting personalized medicine, such as patient-specific Digital Twins. However, realizing their full impact requires addressing current limitations, particularly the technical and ethical challenges unique to medical data.

This session aims to create a collaborative forum to discuss recent advancements, share practical insights, and address the challenges researchers and practitioners face in applying FMs to medical applications. We invite submissions presenting novel methods, experimental findings, and theoretical contributions from both academia and industry. Accepted papers will undergo peer review and will be presented at the conference.

Topics

Topics include but are not limited to:

• Pre-training Strategies for Medical Foundation Models: Techniques for training models on large-scale biomedical datasets, self-supervision, and adapting pre-trained models from general domains to specific medical applications.

• Foundation Models for Medical Imaging: Applications of FMs in radiology, pathology, and other medical imaging domains.

• Foundation Models for Medical Time Series: Techniques for leveraging FMs to analyze time-series data such as physiological signals, vital signs, and ECG data for continuous monitoring, early diagnosis, and personalized treatment planning.

• Large Language Models in Healthcare: Applications of LLMs for clinical decision support, patient engagement, and knowledge retrieval from electronic health records.

• Multimodal Foundation Models in Healthcare: Approaches to integrate data from diverse sources (e.g., imaging, genomic, and clinical data) into FMs to achieve more holistic and accurate medical insights.

• Interpretable AI in Medical Foundation Models: Techniques for explaining complex model decisions and ensuring trust in clinical settings.

• Ethical Implications of Foundation Models in Healthcare: Discussing ethical concerns such as data privacy and bias must be addressed to ensure fair and equitable healthcare for diverse populations.

Submission Guidelines

Please follow the IJCNN 2025 submission guidelines for paper formatting and submission procedures: https://2025.ijcnn.org/authors/call-for-papers. To submit your paper to the Foundation Models in Medicine (FMM) special session, ensure that you select Foundation Models in Medicine (FMM) as the primary subject area.

Submit Paper! 

Accepted papers will be published in the IEEE Xplore Digital Library as part of the IJCNN 2025 proceedings.

Important Dates

• Paper Submission Deadline: January 30, 2025

• Notification of Acceptance: March 17, 2025 

• Conference Dates: June 30-July 5, 2025 | Rome, Italy 

Contact Information

For any questions regarding the special session, please contact: aurora.rofena@unicampus.it