AIM for Dermatology is a research group within the AIM for Health Lab at Monash University focused on developing computational methods that transform how skin diseases are detected, understood, and managed. By combining large-scale clinical datasets with advances in artificial intelligence, our work aims to improve skin cancer screening, dermatological diagnosis, and disease prognosis, while also using skin data to study biological aging and systemic health.
We drive clinical impact through a powerful global network of academic, clinical, and industry partners — including the ACEMID network (Australia's largest melanoma initiative), Alfred Health, Harvard Medical School, Memorial Sloan Kettering, and industry leaders like Canfield Scientific and MoleMap. These collaborations enable us to train and rigorously evaluate our algorithms on diverse, real-world multimodal data. Together with our partners, we are translating methodological breakthroughs into practical tools: from building dermatology foundation models and clinical reasoning systems for general skin conditions, to exploring the emerging frontier of "dermatomics" — investigating how skin phenotypes and imaging might reveal hidden systemic disease risks and aging trajectories.
The AIM for Health Lab (Augmented Intelligence and Multimodal Analytics for Health) is founded and directed by A/Prof. Zongyuan Ge. The lab spans expertise in health AI translation, privacy-preserving AI, federated learning, and multimodal data analysis, with deep connections to first-tier healthcare providers and industry partners. Research from the lab has been published in leading venues including Nature Medicine, Nature Nanotechnology, Science Advances, The Lancet Digital Health, and top AI conferences such as NeurIPS, CVPR, ICCV, ICLR, EMNLP, ACL, and MICCAI.
