FOUNDATION MODELS FOR BIOMEDICINE

Credit Hours: 3 · Graduate

An introduction to foundation models and large-scale machine learning approaches for biomedical data, focusing on learning scalable representations from complex, high-dimensional biomedical data. Topics include applications to biomedical text, imaging, molecular and omics data, multimodal learning, and agent-based systems for healthcare and biological discovery. Recommended Prerequisite(s): Familiarity with machine learning concepts, basic linear algebra and probability, and experience with programming in Python.