Union with Recursive Feature Elimination: A feature selection framework to improve the classification performance of multi-category causes of death in colorectal cancer-Reference-Cited by-同舟云学术

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Union with Recursive Feature Elimination: A feature selection framework to improve the classification performance of multi-category causes of death in colorectal cancer

Published:2023-12 Issue: Volume: Page:100320
ISSN:0023-6837
Container-title:Laboratory Investigation
language:en
Short-container-title:Laboratory Investigation

Author:

Deng Fei,Zhao Lin,Yu Ning,Lin Yuxiang,Zhang Lanjing^ORCID

Funder

National Science Foundation

Publisher

Elsevier BV

Subject

Cell Biology,Molecular Biology,Pathology and Forensic Medicine

Reference68 articles.

1. Colorectal cancer statistics, 2020;Siegel;CA Cancer J Clin,2020

2. Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer;Liu;Nat Commun,2022

3. Prognostic and predictive molecular biomarkers for colorectal cancer: updates and challenges;Koncina;Cancers,2020

4. American Cancer Society. Colorectal Cancer Facts & Figures 2020-2022. Atlanta: American Cancer Society. 2020.

5. Association of KRAS mutation with tumor deposit status and overall survival of colorectal cancer;Zhang;Cancer Causes Control,2020

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1. Interpretable machine learning models for predicting clinical pregnancies associated with surgical sperm retrieval from testes of different etiologies: a retrospective study;BMC Urology;2024-07-29

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