December 12, 2025
December 12, 2025
Asian Conference on Machine Learning 2025, Taipei, Taiwan
Embedded Files
The AI Revolution and the Medical Frontier
Over the past few years, the development of large-scale foundation models has significantly advanced the state-of-the-art in machine learning. Models trained on massive datasets with labelled images or billions of image-text pairs have become available and shown to be very precise and extremely capable. Moreover, even for huge datasets without labels or annotation, unsupervised learning technologies, such as MAE (Masked Autoencoders), DINO, and CLIP, have demonstrated strong generalization capabilities to a variety of downstream tasks across domains. These approaches follow a prevailing trend known as the scaling law, where model performance improves predictably as model size, dataset scale, and computing power increase.
Why Medical AI is Different
One of the most critical and promising AI application areas is the medical or medicare applications. However, the above-mentioned large-scale foundation model paradigm is practically challenging when applied to medical imaging. Unlike natural image domains that enjoy nearly unlimited access to labeled and unlabeled web-scale data, the medical domain is constrained by strict privacy regulations, heterogeneous data sources, limited patient populations, and the requirement for costly, expert-level annotation. High-quality medical datasets are scarce, and when available, they often suffer from domain shifts, label imbalance, and limited modality coverage. In such settings, bluntly applying scaling laws is not only impractical,but also potentially misleading.
Our Mission
In this workshop, we aim to bring together experts from both areas (AI and medicine) to share their experience on research activities on medical AI and to explore promising technologies. Some of the potential issues for discussion include:
1. Foundation model for small scale medical data domains
2. Multi-modality machine learning for medical data
3. Intelligent medicare helpers and physician co-pilots
4. Robotic supporting capabilities for medical applications
This workshop will invite both international and domestic speakers. We will also openly call for research papers for presentation in the workshop. A panel session is planned to facilitate face-to-face discussions between invited medical professionals and senior AI researchers.
Workshop Activities
Our program will feature invited talks from both international and domestic speakers, presentations from our open call for papers, and a dynamic panel session to facilitate face-to-face discussions between invited medical professionals and senior AI researchers.
By holding this workshop, we hope to bring AI researchers and medical professionals together to explore the most important AI research issues for medicine.
Important Dates
Abstract Submission Deadline: October 12, 2025
Author Notification: October 20, 2025
Camera-ready Poster and Short Paper Submission Deadline: November 30, 2025
Workshop Date: December 12, 2025
Contact Us
Ms. Sue Liu
Chang Gung University
Email: aic@gap.cgu.edu.tw
Page updated
Google Sites
Report abuse