Prediction of Ovarian Cancer Response to Therapy Based on Deep Learning Analysis of Histopathology Images.

ABSTRACT:

Background

Ovarian cancer remains the leading gynecological cause of cancer mortality. Predicting the sensitivity of ovarian cancer to chemotherapy at the time of pathological diagnosis is a goal of precision medicine research that we have addressed in this study using a novel deep-learning neural network framework to analyze the histopathological images.

Methods

We have developed a method based on the Inception V3 deep learning algorithm that complements other methods for predicting response to standard platinum-based therapy of the disease. For the study, we used histopathological H&E images (pre-treatment) of high-grade serous carcinoma from The Cancer Genome Atlas (TCGA) Genomic Data Commons portal to train the Inception V3 convolutional neural network system to predict

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10452505 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature