Foundations in Biomedical Informatics II
4 credits, Spring Semester
Artificial intelligence is poised to enable breakthroughs in science and reshape medicine. This introductory course provides a survey of artificial intelligence for biomedical informatics, covering methods for key data modalities: clinical data, networks, language, and images. It introduces machine learning problems from a practical perspective, focusing on tasks that drive the adoption of machine learning in biology and medicine. It outlines foundational algorithms and emphasizes the subtleties of working with biomedical data and ways to evaluate and transition machine learning methods into biomedical and clinical implementation. An important consideration in this course is the broader impact of artificial intelligence, particularly topics of bias and fairness, interpretability, and ethical and legal considerations when dealing with artificial intelligence.
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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