Health AI Central
Peer-Reviewed Publication
Sci Rep2025;15(1):14437.April 25, 2025Journal Article

A pioneering artificial intelligence tool to predict treatment outcomes in ovarian cancer via diagnostic laparoscopy.

Xiaotian Ma1, Yu-Chun Hsu1, Amma Asare2, Kai Zhang1, Deanna Glassman2, Katelyn F Handley3, Katherine Foster4, Khwahish Sharma2, Shannon Westin2, Amir Jazaeri2, Nicole D Fleming2, Pratip K Bhattacharya5, Xiaoqian Jiang1, Anil K Sood2, Shayan Shams6
1McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
2Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
3Department of Gynecologic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
4CHI Saint Joseph Medical Care, Lexington, KY, USA.
5Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
6McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA. shayan.shams@uth.tmc.edu.
PubMed PMC DOI PDF

Abstract

Ovarian cancer is associated with high rates of patient mortality and morbidity. Laparoscopic assessment of tumor localization can be used for treatment planning in newly diagnosed high-grade serous ovarian carcinoma (HGSOC). While spread to multiple intra-abdominal areas is correlated with worse outcomes, whether other morphological tumor differences are also associated with patient outcomes is u…

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