In this upper-division undergraduate course, students will build expertise in developing machine-learning tools to address challenges in health care. The course emphasizes both “how to formulate computational problems”, and “how to develop solutions”. This requires strong foundations in health care and machine learning methods. On the health side, we’ll get clinical guest lectures exploring diverse challenges, with perspectives from the front lines (primary and specialty) care, the diagnosis workflow, treatment selection, and post-treatment follow-ups. On the machine learning side, the course will cover machine learning and deep learning foundations, state-of-the-art neural networks, and then advanced research topics. The course will emphasize rigorous evaluation, algorithmic bias, deployment, and auditing.
Note: tentative schedule is subject to change.
| Lecture Number | Date | Theme | Lecturer |
|---|---|---|---|
| 1 | Aug 28, Thurs | Introduction and Welcome [slides] | Adam Yala |
| 2 | Sep 2, Tues | ML Foundations I [slides] | Adam Yala |
| 3 | Sep 4, Thurs | Primary Care: The Frontlines of Care [slides] | Ida Sim, MD |
| 4 | Sep 9, Tues | ML Foundations II [slides] | Adam Yala |
| 5 | Sep 11, Thurs | AI in Emergency Medicine and Insurance | Casey Ross (Reporter, STAT News) |
| 6 | Sep 16, Tues | NN Foundations I [slides] | Natalia Harguindeguy (PhD Candidate) |
| 7 | Sep 18, Thurs | NN Foundations II [slides] | Natalia Harguindeguy (PhD Candidate) |
| 8 | Sep 23, Tues | AI for Radiology | Jae Sohn, MD |
| 9 | Sep 25, Thurs | Modeling Images and Volumes: Convolutional Neural Networks [slides] | Adam Yala |
| 10 | Sep 30, Tues | Advanced Imaging I [slides] | Adam Yala |
| 11 | Oct 2, Thurs | Advanced Imaging II [slides] | Adam Yala |
| 12 | Oct 7, Tues | Advanced Imaging III [slides] | Adam Yala |
| 13 | Oct 9, Thurs | AI for Cardiology | William Hou (PhD Candidate) |
| 14 | Oct 14, Tues | AI for Cancer Pt 1 [slides] | Adam Yala |
| 15 | Oct 16, Thurs | AI for Cancer Pt 2 [slides] | Adam Yala |
| 16 | Oct 21, Tues | Case Study: AI and Radiology I [slides] | Irene Chen |
| 17 | Oct 23, Thurs | Case Study: AI and Radiology II [slides] | Irene Chen |
| 18 | Oct 26, Tues | Electronic Health Records [slides] | Irene Chen |
| 19 | Oct 28, Thurs | Other Health Data Sources [slides] | Irene Chen |
| 20 | Nov 4, Tues | Benchmarking [slides] | Irene Chen |
| 21 | Nov 6, Thurs | Algorithmic Ethics / Bias | Irene Chen |
| 22 | Nov 11, Tues | No class – Administrative Holiday | |
| 23 | Nov 13, Thurs | FDA Regulatory and Approvals Process | Irene Chen |
| 24 | Nov 18, Tues | Monitoring | Irene Chen |
| 25 | Nov 20, Thurs | Interpretability 1 | Irene Chen |
| 26 | Nov 25, Tues | Interpretability 2 (virtual) | Irene Chen |
| 27 | Nov 27, Thurs | No class – Thanksgiving | |
| 28 | Dec 2, Tues | Additional Health ML Case Studies (virtual) | Irene Chen |
| 29 | Dec 4, Thurs | Open Questions in Machine Learning for Healthcare | Irene Chen |
| Week | Deadline | Date | Time |
|---|---|---|---|
| 4 | Project 1 Released | Tuesday, Sep 16 | |
| 4 | Project 1 Due | Tuesday, Sep 23 | 7:00 PM PT |
| 8 | Project 2 Released | Tuesday, Oct 7 | |
| 8 | Project 2 Due | Thursday, Oct 23 | 7:00 PM PT |
| 10 | Non-Graded Project Check-In Due | Tuesday, Nov 18 | 7:00 PM PT |
| 15 | Non-Graded Project Check-In Feedback Given | Tuesday, Nov 25 | |
| 16 | Final Project Due | Thursday, Dec 11 | 7:00 PM PT |
From UC Berkeley’s Academic Accommodations Hub: UC Berkeley is committed to creating a learning environment that meets the needs of its diverse student body. Students who anticipate or experience barriers to learning are encouraged to contact the Disabled Students’ Program (DSP) to determine authorized academic accommodations. The DSP is located at 260 César E. Chávez Student Center, phone (510) 642-0518, URL https://dsp.berkeley.edu.
If you already have a DSP accommodation letter, please share it with the instructors as early as possible so that we can work with you and DSP to ensure appropriate arrangements are in place.
If you are experiencing personal, academic, or emotional difficulties, you are encouraged to reach out to Counseling and Psychological Services (CAPS) through University Health Services at the Tang Center. CAPS provides confidential counseling, crisis intervention, and mental-health resources for Berkeley students. Appointments can be made by calling (510) 642-9494 or visiting the CAPS website.
