Tentative Schedule

DateTopicLecture Slides
Lecture 1 Sept 17 (Thur) Course introduction: why machine learning in healthcare? BIODS388_Lecture_1.pdf
Session Sept 18 (Fri) Project partner finding session (for students taking 3 units)
Lecture 2 Sept 24 (Thur) Machine learning framework: terms, definitions, and jargon BIODS388_Lecture_2.pdf
Lecture 3 Oct 1 (Thur) Supervised machine learning and traditional approaches BIODS388_Lecture_3.pdf
Assignment Oct 7 (Wed) Due: Scientific paper review 1
Lecture 4 Oct 8 (Thur) Fundamentals of deep learning and neural networks BIODS388_Lecture_4.pdf
Project Oct 9 (Fri) Due: Project Proposal
Guest lecture Oct 12 (Mon) Strategies for Interdisciplinary Projects in AI and Healthcare
Lecture 5 Oct 15 (Thur) Common neural network architectures for different clinical applications BIODS388_Lecture_5.pdf
Lecture 6 Oct 22 (Thur) Evaluation metrics for machine learning in healthcare BIODS388_Lecture_6.pdf
Assignment Oct 28 (Wed) Due: Scientific paper review 2
Lecture 7 Oct 29 (Thur) Strategies, challenges, and the black box BIODS388_Lecture_7.pdf
Project Oct 30 (Fri) Due: Project Milestone
Lecture 8 Nov 5 (Thur) Data considerations for clinical machine learning BIODS388_Lecture_8.pdf
Lecture 9 Nov 12 (Thur) Team-based design and evaluation of clinical machine learning applications BIODS388_Lecture_9.pdf
Project Nov 18 (Wed) Due: Project Report
Presentations Nov 18 (Wed) Project Presentations with BIODS220
Lecture 10 Nov 19 (Thur) Course conclusion: the future of clinical work in the era of machine learning BIODS388_Lecture_10.pdf