CS 523: Research Seminar in Computer Vision and Healthcare
Stanford University, Spring 2020-2021
[see on ExploreCourses] With advances in deep learning, computer vision (CV) has been transforming healthcare, from diagnosis to prognosis, from treatment to prevention. Its far-reaching applications include surgical assistants, patient monitoring, data synthesis, and cancer screening. Before these algorithms make their way into the clinic, however, there is exciting research to develop methods that are accurate, robust, interpretable, grounded, and human-centered. In this seminar, we deeply examine these themes in medical CV research through weekly intimate discussions with researchers from academia and industry labs who conduct research at the center of CV and healthcare. Each week students will read and prepare questions and reflections on an assigned paper authored by that week's speaker. We highly encourage students who are interested in taking an interactive, deep dive into medical CV research literature to apply. While there are no hard requirements, we strongly suggest having the background and fluency necessary to read and analyze AI research papers (thus MATH 51 or linear algebra, and at least one of CS 231x, 224x, 221, 229, 230, 234, 238, AI research experience for CV and AI fundamentals may be helpful).
This course aims to bring together enthusiasts and interested students in an intimate setting to deeply discuss medical computer vision research. As a result, an active presence in each course session and completion of the required assignments is required to pass the class. We value open communication, so if you have special circumstances, of course please let me know! :)
Unless otherwise specified, the assignments due before each class session are the following:
(1) Carefully read this week's assigned paper written by this week's speaker.
(2) By 11:59pm PST the day before, post to Canvas at least 5 pre-discussion points regarding the paper; these must be from at least two different categories below. Students who signed up to be the Q&A representatives are required to ask their questions to the speaker this week!
- A meaty (not just yes/no) question,
- An insight or analytical comment about the paper,
- A key finding or contribution of the paper,
- A concern or constructive comment about the paper,
- A related paper it reminds you of that you want to share (and why).
(3) Write a few-sentence reflection on the previous week's session, focusing on what you learned from the session that you didn’t realize prior to talking directly with the paper author.
(4) Add your short (1-2 sentence) thank-you note to the post-session thank-you sheet for the previous week’s speaker.
|Date||Paper + Announcements||Speaker(s)|
Q&A representative sign-ups sent out to students after class!
|Prof. Serena Yeung, Stanford University (MARVL)|
Additional final assignment: write a paragraph reflection on what you took from the course, the paper/speaker(s) you found most interesting and why, and constructive feedback.