The MaML Podcast - Medicine & Machine Learning23 Aug 2021

James Zou - Using AI to Better Inclusion Criteria for Clinical Trials and Data Valuation

Dr. James Zou of Stanford University is an inaugural Chan-Zuckerberg investigator and faculty director for the university-wide AI for Health program.

Dr. Zou recently published a paper in Nature which is making waves in the clinical trial world because it is causing us to rethink how we set eligibility criteria for clinical trials. Using an ML approach, he shows that by changing such criteria, we can make trials both more inclusive, opening them up to way more patients, while at the same time safeguarding patient safety.

We also talk about his various other research projects, which span the gamut from evaluating FDA approvals of AI algorithms, all the way to deeper mathematical concepts like data valuation. Dr Zou is an impressive titan in the AI and medicine space. In this interview I really came to appreciate how broad his research spans, which I think is key to his many successful projects. We ultimately close with some good advice for people looking to get involved in this exciting and growing space.

02:45 Introduction to the intersection of Medicine and AI

4:20 Life after Ph.D.

6:35 New Nature paper on AI and clinical trials

13:25 How did we approach this question?

14:15 Data Driven Approach - Trial Path Finder

16:59 The ethical implications of this approach

19:35 Why are minority populations excluded from research?

20:25 Using AI to include ineligible patients in clinical trials

23:50 Future for this project

27:00 Evaluation of FDA approvals for AI algorithms

32:23 Favorite Project Dr. Zou has worked on

35:01 Dr. Zou's favorite math concept in the machine learning space

39:10 Separating signal from noise

39:53 Dream research projects

41:00 Future of Ai % medicine in 10-20 years

43:15 The human and AI team

47:40 What advice would you give to your 20 year old self

Interviewer: David Wu

Producer: Aaron Schumacher & Alexander Jacobs

Art: Melanie Bussan

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