Helping out with the new building 👷♂️👷♀️ With Erdem Bıyık Swabha Swayamdipta Ibrahim Sabek Ruishan Liu
How can we use ML to optimize clinical trial designs & identify genetic biomarkers for precision oncology?
Watch this talk by Ruishan Liu from StanfordDBDS as she discusses her work on ML for clinical trials & precision medicine.
youtube.com/watch?v=0dt3S2…
Join us for the USC Symposium on Frontiers of Generative AI Models in Science and Society!
Featuring special guests Alessandro Vespignani Nitesh Chawla Yizhou Sun Jian Ma & Robin Jia Yue Wang Ruishan Liu USC Viterbi School
📅 Mar 25
📍MCB 101
🔗RSVP (limited space) tinyurl.com/4zpmfysa
This week, Ruishan Liu from Stanford will be joining us to talk about AI for clinical trials and precision medicine. Catch it at 1-2pm PT this Thursday on Zoom!
Subscribe to mailman.stanford.edu/mailman/listin…
#ML #AI #medicine #healthcare
This Monday, Jan. 22 USC ISI! Our very own Ruishan Liu will speak on 'Optimizing Clinical Trial Design: The Role of AI in Boosting Inclusivity and Efficiency.'
Learn more and register 👇
isi.edu/events/4316/AI…
USC Viterbi School USC Research and Innovation
James Zou Ruishan Liu Dr Shemra Rizzo Sarah Waliany, MD, MS Navdeep Pal Zhi Huang Joel W. Neal, MD, PhD adding a little - how did you interpret results for mutually exclusive mutation pairs? For example KRAS and EGFR are almost never co-mutated - thus I would interpret the results for KRAS being protective in EGFR treatment setting as spurious curious what you think.
We are delighted to introduce 10 new faculty members to USC Thomas Lord Department of Computer Science this academic year!⭐️
Get to know a little bit about them ⬇️
viterbischool.usc.edu/news/2023/09/t…
Erdem Bıyık Ruishan Liu Evi Micha Willie Neiswanger Ibrahim Sabek Daniel Seita 🇺🇦 Yue Wang Jieyu Zhao Yue Zhao USC Viterbi School
What a privilege working w/ James Zou Ruishan Liu Joel W. Neal, MD, PhD on this analysis of genomic alterations predicting outcomes across 8 cancer types, identifying known & unknown mutation-treatment & mutation-mutation interactions #precisiononcology Stanford Cancer Institute Stanford Department of Medicine
USC Thomas Lord Department of Computer Science Gaurav Sukhatme Alessandro Vespignani Nitesh Chawla Yizhou Sun Jian Ma Robin Jia Yue Wang Ruishan Liu USC Viterbi School Wow, bravo! Our journal is also interested in exploring and expanding in this field, do you have online live? We wonder if we have the honor and chance to audit. Additionally, if possible, we hope we can collaborate in later symposium!
Thank you everyone for joining us today! Ruishan Liu 's talk is now available on our YouTube channel: youtube.com/watch?v=9HVKmT…
Topics included:
1. De novo antibiotic discovery, led by Kyle Swanson 💊, molecules were validated to inhibit 4/6 ESKAPE pathogens at <= 8 ug/mL.
2. Design of eligibility criteria for oncology clinical trials, led by Ruishan Liu 🏥
Paper at nature.com/articles/s4158…. 2/4
USC Thomas Lord Department of Computer Science Erdem Bıyık Ruishan Liu Evi Micha Willie Neiswanger Ibrahim Sabek Daniel Seita 🇺🇦 Yue Wang Jieyu Zhao Yue Zhao USC Viterbi School How much diversity was considered in the process! From the school/affiliation perspective?
Ruishan Liu develops #ML for #precisionmedicine . web.stanford.edu/~ruishan/
Ruishan was one of my 1st PhDs and she’s superstar. Her 1st author paper nature makes clinical trials more inclusive nature.com/articles/s4158… #datascience . It won 2022 Top 10 Clinical Research Achievement.
💡Key idea is to start w/ a small core group of data and grow the subset while monitoring test statistics. We call this algorithm DDGroup.
It has strong statistical guarantees and works well on diverse social science and biomedical data. Great work by Zach Izzo + Ruishan Liu!
James Zou Ruishan Liu Dr Shemra Rizzo Sarah Waliany, MD, MS Navdeep Pal Zhi Huang Joel W. Neal, MD, PhD Congrats on the paper! Awesome to see academia + industry collabs. I was curious if you tried controlling for other potential molecular confounders in your work - e.g. TMB or MSI come to mind as factors potentially generating mutations and are known to be predictive of response
Wonderful team led by Ruishan Liu Dr Shemra Rizzo Sarah Waliany, MD, MS Maris Garmhausen, Navdeep Pal, Zhi Huang, Nayan Chaudhary, Lisa Wang, Chris Harbron, Joel W. Neal, MD, PhD and Ryan Copping!