Applying machine learning techniques to predict the risk of lung metastases from rectal cancer: a real-world retrospective study.

ABSTRACT:

Background

Metastasis in the lungs is common in patients with rectal cancer, and it can have severe consequences on their survival and quality of life. Therefore, it is essential to identify patients who may be at risk of developing lung metastasis from rectal cancer.

Methods

In this study, we utilized eight machine-learning methods to create a model for predicting the risk of lung metastasis in patients with rectal cancer. Our cohort consisted of 27,180 rectal cancer patients selected from the Surveillance, Epidemiology and End Results (SEER) database between 2010 and 2017 for model development. Additionally, we validated our models using 1118 rectal cancer patients from a Chinese hospital to evaluate model performance and generalizability. We assessed our models' performan

SUBMITTER: Qiu B 

PROVIDER: S-EPMC10247137 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature