Predicting ovarian cancer without artificial intelligence: What 409,780 patients taught us

Journal article

Peer reviewed

Chelsea Stewart, John Chan, Caitlin Johnson, Jonathan Lancaster, Dana Chase, Daniel Kapp and Cheng-I Liao

Gynecologic oncology, Vol.190, pp.S362-S363

11/2024

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Title: Predicting ovarian cancer without artificial intelligence: What 409,780 patients taught us
Creators: Chelsea Stewart - University of California, Los Angeles
John Chan - California Pacific Medical Center, San Francisco, CA, United States
Caitlin Johnson - California Pacific Medical Center, San Francisco, CA, United States
Jonathan Lancaster - George Washington University
Dana Chase - University of California, Los Angeles
Daniel Kapp - Stanford University
Cheng-I Liao - Pingtung Veterans General Hospital, Pingtung, Taiwan
Publication Details: Gynecologic oncology, Vol.190, pp.S362-S363
Publisher: Elsevier Inc
Identifiers: 991006118332402656
Academic Unit: Obstetrics & Gynecology
Language: English
Resource Type: Journal article