Foundations in Biomedical Informatics II

4 credits, Spring Semester

Artificial intelligence is poised to reshape medical research and clinical care. This course offers a comprehensive overview of modern AI in biology and medicine. By delving into key data modalities, including genomics, molecular structures and sequences, patient-level clinical data, natural language, and images, this course covers AI foundations and cutting-edge advances, including large language models, self-supervised learning, geometric deep learning, and generative AI, from a hands-on, practical viewpoint. Students will gain a deep understanding of AI methods while grasping the nuances of working with biomedical data, effectively evaluating AI models, and transitioning AI systems into clinical and research practice. Broader impacts of AI are an important consideration for this course, particularly topics of human-AI collaboration, bias and fairness, interpretability, and ethical and legal considerations when dealing with artificial intelligence in medicine.

Course website: https://zitniklab.hms.harvard.edu/BMI702 

BMI 702 is only open to students in the Master of Biomedical Informatics program.

Prerequisites: BMI 701 and BMI 713 or equivalent. 

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