Application of deep learning to the classification of images from colposcopy.

The objective of the present study was to investigate whether deep learning could be applied successfully to the classification of images from colposcopy. For this purpose, a total of 158 patients who underwent conization were enrolled, and medical records and data from the gynecological oncology database were retrospectively reviewed. Deep learning was performed with the Keras neural network and TensorFlow libraries.

The concept of platinum sensitivity could be applied to recurrent cervical cancer: a multi-institutional retrospective study from the Japanese Gynecologic Oncology Group.

Purpose: This study aimed at evaluating the applicability of the concept of platinum sensitivity to recurrent cervical cancer.

Methods: The clinical information of patients with recurrent cervical cancer, who were initially treated with platinum-based chemotherapy and received second-line platinum-based chemotherapy at the time of recurrence between January 2008 and December 2012, was retrospectively reviewed.

Results: A total of 677 patients from 71 medical centers were analyzed.