Sone Kenbun, Toyohara Yusuke, Taguchi Ayumi, Miyamoto Yuichiro, Tanikawa Michihiro, Uchino-Mori Mayuyo, Iriyama Takayuki, Tsuruga Tetsushi, Osuga Yutaka
Department of Obstetrics and Gynecology, Faculty of Medicine, The University of Tokyo, Tokyo, Japan.
J Obstet Gynaecol Res. 2021 Aug;47(8):2577-2585. doi: 10.1111/jog.14818. Epub 2021 May 10.
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.
随着机器学习和深度学习模型的发展，人工智能目前正被应用于医学领域。在肿瘤学中，近年来人工智能在医学图像（如放射图像）的诊断评估、利用基因组数据的组学分析以及临床信息方面的应用不断增加。关于人工智能在妇科恶性肿瘤领域应用的报道越来越多，我们对这些研究进行介绍和综述。对于宫颈癌和子宫内膜癌，利用人工智能对阴道镜检查、宫腔镜检查和磁共振图像等医学图像进行评估的报道屡见不鲜。在卵巢癌方面，许多报道将医学图像评估与利用人工智能对临床和基因组数据进行的多组学分析相结合。然而，很少有研究结果能够在临床实践中得到应用，未来还需要进一步研究。
