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Application of artificial intelligence in gynecologic malignancies: A review

Kenbun Sone, Yusuke Toyohara, Ayumi Taguchi, Yuichiro Miyamoto, Michihiro Tanikawa, Mayuyo Uchino‐Mori, Takayuki Iriyama, Tetsushi Tsuruga, Yutaka Osuga

2021Journal of obstetrics and gynaecology research46 citationsDOI

Abstract

With the development of machine learning and deep learning models, artificial intelligence is now being applied to the field of medicine. In oncology, the use of artificial intelligence for the diagnostic evaluation of medical images such as radiographic images, omics analysis using genome data, and clinical information has been increasing in recent years. There have been increasing numbers of reports on the use of artificial intelligence in the field of gynecologic malignancies, and we introduce and review these studies. For cervical and endometrial cancers, the evaluation of medical images, such as colposcopy, hysteroscopy, and magnetic resonance images, using artificial intelligence is frequently reported. In ovarian cancer, many reports combine the assessment of medical images with the multi-omics analysis of clinical and genomic data using artificial intelligence. However, few study results can be implemented in clinical practice, and further research is needed in the future.

Topics & Concepts

ColposcopyMedicineArtificial intelligenceMedical physicsGynecologic oncologyCervical cancerApplications of artificial intelligenceClinical PracticeDeep learningCancerComputer scienceInternal medicineFamily medicineEndometrial and Cervical Cancer TreatmentsRadiomics and Machine Learning in Medical ImagingOvarian cancer diagnosis and treatment