CT-based deep learning model for the prediction of DNA mismatch repair deficient colorectal cancer: a diagnostic study.

ABSTRACT:

Background

Stratification of DNA mismatch repair (MMR) status in patients with colorectal cancer (CRC) enables individual clinical treatment decision making. The present study aimed to develop and validate a deep learning (DL) model based on the pre-treatment CT images for predicting MMR status in CRC.

Methods

1812 eligible participants (training cohort: n = 1124; internal validation cohort: n = 482; external validation cohort: n = 206) with CRC were enrolled from two institutions. All pretherapeutic CT images from three dimensions were trained by the ResNet101, then integrated by Gaussian process regression (GPR) to develop a full-automatic DL model for MMR status prediction. The predictive performance of the DL model was evaluated using the area under the receiver operatin

SUBMITTER: Cao W 

PROVIDER: S-EPMC10035255 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature