Predicting pathologic complete response in locally advanced rectal cancer patients after neoadjuvant therapy: a machine learning model using XGBoost.
Journal Information
Full Title: Int J Colorectal Dis
Abbreviation: Int J Colorectal Dis
Country: Unknown
Publisher: Unknown
Language: N/A
Publication Details
Subject Category: Gastroenterology
Available in Europe PMC: Yes
Available in PMC: Yes
PDF Available: No
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"Declarations Conflict of interestThe authors declare no competing interests. Conflict of interest The authors declare no competing interests."
"Funding This work was supported by the National Key R&D Program of China (No. 2017YFC1308800); National Natural Science Foundations of China (No. 81970482, 81770557, and 82070684); Guangdong Natural Science Fund for Outstanding Youth Scholars (No. 2020B151502067), The Sixth Affiliated Hospital of Sun Yat-Sen University Clinical Research- “1010” Program (No. 1010PY(2020)-63), and National Key Clinical Discipline."
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Tool: rtransparent
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Last Updated: Aug 05, 2025