Use of Artificial Intelligence in the Management of T1 Colorectal Cancer: a New Tool in the Arsenal or is Deep Learning out of Its Depth?

Overview

Journal Clin Endosc

Date 2023 Sep 24

PMID 37743068

Authors

James Weiquan Li

Lai Mun Wang

Katsuro Ichimasa

Kenneth Weicong Lin

James Chi-Yong Ngu

Tiing Leong Ang

Affiliations

Soon will be listed here.

Abstract

The field of artificial intelligence is rapidly evolving, and there has been an interest in its use to predict the risk of lymph node metastasis in T1 colorectal cancer. Accurately predicting lymph node invasion may result in fewer patients undergoing unnecessary surgeries; conversely, inadequate assessments will result in suboptimal oncological outcomes. This narrative review aims to summarize the current literature on deep learning for predicting the probability of lymph node metastasis in T1 colorectal cancer, highlighting areas of potential application and barriers that may limit its generalizability and clinical utility.

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