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Seeing into the future: Machine learning methods for personalized screening (AI PHI Affinity Group)

December 2 @ 9:00 am - 10:00 am

Free

Thank you for coming!

Watch the recording for the December 2023 Affinity Group meeting below.

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Topic

Seeing into the future: Machine learning methods for personalized screening

Effective population cancer screening programs must balance the benefits of early detection against the harms of overscreening, offering screening to those likely to develop cancer and minimizing screening for the rest; this capacity relies on two key technologies, namely risk assessment and screening policy design. Risk models impact millions of patients every year, guiding current screening and prevention efforts. However, current models used clinically primarily rely on categorical features representing patient demographics and clinical history, limiting their predictive capacity. In this talk, I introduce AI tools for risk assessment from imaging and screening policy design and I discuss modeling approaches that are robust to data-generation biases, offer safe-guards for clinical deployment and can adapt to diverse clinical requirements. I’ve demonstrated that these clinical models offer significant improvements over the current standard of care across globally diverse patient populations.

Presented by Adam Yala

Adam Yala an assistant professor of Computational Precision Health and EECS at UC Berkeley and UCSF. His research focuses on developing machine learning methods for personalized medicine and translating them to clinical care. His previous research has contributed to three areas: 1) predicting future cancer risk, 2) designing personalized screening policies and 3) private data sharing through neural obfuscation. Adam’s tools underly multiple prospective trails and his research has been featured in the Washington Post, New York Times, Boston Globe and Wired. Prof Yala obtained his BS, MEng and PhD in Computer Science from MIT and he was a member of MIT Jameel Clinic and MIT CSAIL.

Artificial Intelligence in Cancer Research – AI PHI Affinity Group

(First Friday of each month)

This group was formed to discuss the current trends and applications of artificial intelligence in cancer research and clinical practice. The group brings together AI researchers in a variety of fields (computer science, engineering, nutrition, epidemiology radiology, etc) with clinicians and advocates. Students, trainees and faculty with any or no background in AI are encouraged to attend. The goal is to foster collaborative interactions to solve problems in cancer that were thought to be unsolvable a decade ago before the broad use of deep learning and AI in medicine.

Contact: Dr. John Shepherd at johnshep@hawaii.edu or Peter Washington at pyw@hawaii.edu

 

Details

Date:
December 2
Time:
9:00 am - 10:00 am
Cost:
Free
Event Category:

Venue

Virtual (Zoom)

Organizer

Artificial Intelligence and Precision Health Institute (AI PHI)
View Organizer Website