september, 2021
Event Details
Registration: https://btep.ccr.cancer.gov/classes/ai_four/ Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m5fa0e43ae167ed5ea3a77fb25d339a82 Description: In this talk, we will highlight two examples for building predictive models from multi modal data. The first example predicts dose response in cell
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Event Details
Registration: https://btep.ccr.cancer.gov/classes/ai_four/
Meeting Link: https://cbiit.webex.com/cbiit/j.php?MTID=m5fa0e43ae167ed5ea3a77fb25d339a82
Description: In this talk, we will highlight two examples for building predictive models from multi modal data. The first example predicts dose response in cell lines based on drug and molecular features. The second example will show to combine pathology whole slide images and molecular features for cancer diagnosis and prognosis.
Presenters: George Zaki, Bioinformatics Manager, Strategic and Data Science Initiatives (SDSI), Frederick National Laboratory for Cancer Research (FNL), Pinyi Lu, Bioinformatics analyst, SDSI, FNL
Time
(Thursday) 1:00 pm - 2:00 pm
Location
Online
Organizer
CBIITCBIITDaoud Meerzaman, meerzamd@mail.nih.gov