Results for ANES 212: Machine Learning for Healthcare Quality: Precision Medicine Al Design Lab

This course provides a hands-on introduction to building machine learning systems for healthcare quality analysis and improvement. We explore several unconditional topics, including data representation, data manipulation, data analysis and data visualization. Students will be introduced to these topics during lectures. The course also provides students with a significant opportunity to investigate the application of these ideas to real-world clinical quality improvement challenges. Working with clinical mentors from the Stanford University School of Medicine students will be expected to supplement machine learning theory with a quarter-long project targeting representative clinical quality improvement challenges. Students will be encouraged to think creatively about traditionally hard quality problems and requires to perform group research exposing them to designing practical machine learning systems for healthcare.