Histopathology Images-Based Deep Learning Prediction of Histological Types in Endometrial Cancer.

ABSTRACT:

Background

According to the new 2023 International Federation of Gynecology and Obstetrics staging system for endometrial cancer (EC), EC is classified into aggressive and nonaggressive histological types. Accurate diagnosis of the histological type of EC is crucial for optimizing treatment strategies and predicting patient outcomes.

Objectives

To develop and validate a deep convolutional neural network for predicting nonaggressive versus aggressive histological types from hematoxylin and eosin (H&E)-stained images of EC specimens.

Methods

A deep convolutional neural network named EC-AI^HIS was developed to predict the nonaggressive or aggressive histological type from 1187 EC specimens. Its generalizability and clinical utility were assessed across multiple

SUBMITTER: Li L 

PROVIDER: S-EPMC12753328 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature