Ovarian cancer diagnosis and treatmentAI in cancer detectionChromatin Remodeling and Cancer

E. Ehimiaghe, Hannah L Dimmick, Daniel Spinosa, Freda Ireigbe, Miriam D. Post, R. Wolsky, Aaron Clauset, S. Orsulic, Sarah Taylor, Elena W. Y. Hsieh, N. Davidson, M. Wood, Benjamin G. Bitler, B. Corr, S. Guntupalli, Lindsay W Brubaker, Marisa R. Moroney, K. Behbakht

2026.1.1EUROPEAN JOURNAL OF GYNAECOLOGICAL ONCOLOGY

DOI: 10.22514/ejgo.2026.002

tlooto Summary

Key ways in which systematic integration of Artificial intelligence (AI) and computational tools can be leveraged to improve outcomes in ovarian cancer as well as the limitations and risks of their application are highlighted.

Abstract

Artificial intelligence and computational biology are rapidly advancing, offering unprecedented opportunities to transform both ovarian cancer research and clinical care. However, limited understanding of how to optimally integrate the information these tools provide with existing clinical data has led to a lag in integration. This commentary emerges from a unique and focused ovarian cancer research conference that explored how these emerging tools and technologies ( i.e. , artificial intelligence and computational biology) can be leveraged to address questions in pathology, develop new paradigms of tumor biology, and integrate precision medicine into clinical management of complex and rare subtypes of ovarian cancer. We highlight key ways in which systematic integration of Artificial intelligence (AI) and computational tools can be leveraged to improve outcomes in ovarian cancer as well as the limitations and risks of their application.

Citation format

EHIMIAGHE, E., et al. Ovarian cancer think tank: The use of integrated artificial intelligence and computational biology in ovarian cancer diagnosis and treatment. EUROPEAN JOURNAL OF GYNAECOLOGICAL ONCOLOGY, 2026, 47(1): 15.