Colorectal cancer risk stratification on histological slides based on survival curves predicted by deep learning.

ABSTRACT: Studies have shown that colorectal cancer prognosis can be predicted by deep learning-based analysis of histological tissue sections of the primary tumor. So far, this has been achieved using a binary prediction. Survival curves might contain more detailed information and thus enable a more fine-grained risk prediction. Therefore, we established survival curve-based CRC survival predictors and benchmarked them against standard binary survival predictors, comparing their performance extensively on the clinical high and low risk subsets of one internal and three external cohorts. Survival curve-based risk prediction achieved a very similar risk stratification to binary risk prediction for this task. Exchanging other components of the pipeline, namely input tissue and feature extractor, had l

SUBMITTER: Hohn J 

PROVIDER: S-EPMC10522577 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature