“…62 Such AI-assisted imaging-related clinical tasks can increase the efficiency of health-care delivery by reducing the cognitive burden of human experts. 63 In the latest research mentioned in this review, it is found that the application performance of AI in gynecologic oncology at present mostly exceeds the existing methods and models in prognosis and diagnosis 21,27,29,31,53,54,[56][57][58][59][60] and it is also superior to the less experienced clinicians, 20 or equivalent to the most experienced clinicians. 22,23,30 In the comparison of AI itself, it is also found that the performance of the ensemble classifier combining DL and SL is often the best, 28,34 DL (ANN, CNN, FFBPNN, and PNN, etc) is often better than SL (CARTs, SVM, and RF, etc), 20,21,26,29,57,59 but a small part of them are the same 28 or even the opposite.…”