Binghamton University 3 credits BME
This is a lecture-based course for biomedical engineering students interested in learning and applying artificial intelligence (AI) approaches to real-world biomedical problems. The course focuses on principles of a number of AI and machine learning tools such as clustering, regression, decision trees, random forests and neural networks and their applications in various areas of biomedical engineering, such as biomedical data analysis, disease diagnosis, clinical risk stratification, disease progression modeling, patient outcome prediction, and phenotype and biomarker discovery. Students will use various computational tools to manipulate large data sets as part of homework assignments and projects. Prerequisites: MATH 227 (Cal II), BME 203 and BME 340 or instructor approval. Fall semester. 3 credit hours.
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