Artificial Intelligence (AI) is revolutionizing healthcare, and at the heart of this transformation are foundation models (FMs), large-scale deep learning systems trained on massive datasets and a more general form of chatGPT beyond text. In their recent paper, A Comprehensive Survey of Foundation Models in Medicine accepted by IEEE Reviews in Biomedical Engineering (RBME), researchers Ruogu Fang, Associate Professor and Pruitt Family Endowed Faculty Fellow in the J. Crayton Pruitt Family Department of Biomedical Engineering, along with her Postdoc Associate Wasif Khan, provide an in-depth exploration of these models, their applications, and the challenges they present in modern medicine.

FMs have shifted the way researchers approach AI, evolving beyond specialized, task-specific algorithms to generalizable systems capable of performing multiple functions with minimal additional training. While large language models (LLMs) such as ChatGPT and Gemini have taken center stage, foundation models extend beyond text, spanning fields such as medical imaging, genomics, drug discovery, and clinical decision support.

“Foundation models are transforming our perception of AI and the way we interact with different modalities of data such as satellite images, neuroimaging, genomics, and social networks, just like chatGPT changed the way of interaction with text in late 2022” says Ruogu Fang.

Read the full article at Norman Fixel Institute for Neurological Diseases >>