BME 571 Machine Learning in Biomedical Engineering

Machine learning, a major branch of artificial intelligence (AI), has empowered scientists and clinicians to automatically visualize and analyze critical information in biomedical applications. Recently, rapid developments in advanced computing and imaging system in biomedical areas have given rise to a new research dimension with increasing size of biomedical data that requires precise machine learning-based algorithms for biomedical tasks. The overall goal of this course is to help students gain comprehensive understandings of machine learning, including supervised learning, unsupervised learning, dimensionality reduction, decision tree, deep learning, etc. This course will introduce machine learning-related topics in AI with a focus on its applications in biomedical engineering such as biomedical imaging processing. Furthermore, students will use programming languages to implement machine learning technology. This course will also review the progress of machine learning in multiple biomedical engineering directions, such as medical/biomedical image analysis, image reconstruction, tissue engineering, neural engineering, biomechanics, etc.




School of Systems and Enterprises

Typically Offered Periods

Fall Semester Spring Semester Summer Semester