Exploration of applications of data analytics, machine learning, and deep learning in health sciences and biomedical data; topics include theoretical foundations, algorithms and methods of deriving valuable insights from data, predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Prerequisites: Grade of C or better in BMEN 207 and BMEN 250 or STAT 312; Biomedical Engineering major Credits 3. 3 Lecture Hours.
Exploration of applications of data analytics, machine learning, and deep learning in health sciences and biomedical data; topics include theoretical foundations, algorithms and methods of deriving valuable insights from data, predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Prerequisites: Grade of C or better in BMEN 207 and BMEN 250 or STAT 312; Biomedical Engineering major Credits 3. 3 Lecture Hours.
