Predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer with two step feature selection and ensemble learning

Predicting pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer with two step feature selection and ensemble learning

Abstract Patients with locally advanced rectal cancer (LARC) show substantial individual variability and a pronounced imbalance in response distribution to neoadjuvant chemoradiotherapy (nCRT), posing significant challenges to treatment response prediction. This study aims to identify effective pred...

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Bibliographic Details
Main Authors: Changshun Qian, Shuxin Yang, Yijing Chen, Ran Ge, Fangmin Shi, Chengnan Liu, Hui Wang, You Guo
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Feature selection
Locally advanced rectal cancer
Neoadjuvant chemoradiotherapy
Class imbalance problem
Ensemble learning
Online Access:https://doi.org/10.1038/s41598-025-94337-y
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https://doi.org/10.1038/s41598-025-94337-y

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