BE400/500: Machine Learning for Biomedical Data

A technical introduction to pattern classification and machine learning, focusing on biomedical data.

Students will learn the details of classical and modern machine learning approaches and when to apply them. We will focus on applications to biomedical problems, including quantification, disease diagnosis, patient classification, and decision support systems.

The lecture material will be a mix of theory and application, with both lecture notes and in-class demos used to describe the concepts behind each of the algorithms we will discuss. The goal is for students to feel confident in selecting and applying machine learning algorithms to problems in biomedical engineering.


About

I am Assistant Professor of Pathology and Anatomical Sciences, Biomedical Engineering, and Biomedical Informatics at the University at Buffalo, SUNY. My lab develops computational tools for medical data, with a focus on imaging, machine learning, and artificial intelligence.

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