Bioengineering Applications in Machine Learning

3 Credits

Introduction to machine learning and AI techniques as well as their applications in biomedical data quantification, prediction, and visualization. Topics include principles of bioengineering data modalities and systems, fundamentals of machine learning approaches for biomedical data analysis, such as denoising, standardization, statistical analysis, dimensionality reduction, predictive modeling, as well as computational tools for implementing AI methods. Prerequisites: MATH 205 and PHY 021