Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study

A machine learning model constructed using preoperative laboratory tests and clinical and pathological features can assist in predicting the 5-year recurrence risk of patients with stage III colon cancer. This model provides potential reference values for the clinical development of individualized treatment strategies.

Authors

Institutions

Publication Details

Journal
BMC Gastroenterology
Published
2026-01-29
DOI
https://doi.org/10.1186/s12876-025-04511-9
Primary Topic
Colorectal Cancer Surgical Treatments
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study

Xi Wu, Xihao Fu, Li Xu, Hangping Wei et al.
BMC Gastroenterology
Colorectal Cancer Surgical Treatments
article

Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study

Xi Wu, Xihao Fu, Li Xu, Hangping Wei, Xinkai Wu, Yuanyuan Cheng
article en

Abstract

A machine learning model constructed using preoperative laboratory tests and clinical and pathological features can assist in predicting the 5-year recurrence risk of patients with stage III colon cancer. This model provides potential reference values for the clinical development of individualized treatment strategies.

BMC GastroenterologyVol. 26(1)
Wenzhou Medical University (CN), Soochow University (CN), Zhejiang Cancer Hospital (CN), First Affiliated Hospital of Soochow University (CN), Dongyang People's Hospital (CN)
Jinhua Science and Technology Bureau
Openalex Percentile: Top 74%
Colorectal Cancer Surgical Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study — Xi Wu, Xihao Fu, et al. · BMC Gastroenterology (2026) | TGRS Research Map | TGRS