Combining Genetic and Nongenetic Prognostic Factors for Colon Cancer Classification

This study attempted to classify colon cancer using both genetic and nongenetic prognostic factors. RFS rate difference was adopted as a method for selecting and combining these factors. Four leaf classes, II/T3, II/T4, III/KRAS-wt, and III/KRAS-mut were obtained from the discovery cohort. Significant RFS rate differences were also observed among leaf classes in the validation cohort, which is superior to the classifications of TNM staging and the classifications based on biomarkers and gene expressions.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/cisp-bmei64163.2024.10906234
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Combining Genetic and Nongenetic Prognostic Factors for Colon Cancer Classification

Meng Pan, Jie Zhang
Radiomics and Machine Learning in Medical Imaging
article

Combining Genetic and Nongenetic Prognostic Factors for Colon Cancer Classification

Meng Pan, Jie Zhang
article en

Abstract

This study attempted to classify colon cancer using both genetic and nongenetic prognostic factors. RFS rate difference was adopted as a method for selecting and combining these factors. Four leaf classes, II/T3, II/T4, III/KRAS-wt, and III/KRAS-mut were obtained from the discovery cohort. Significant RFS rate differences were also observed among leaf classes in the validation cohort, which is superior to the classifications of TNM staging and the classifications based on biomarkers and gene expressions.

Jinan University (CN)
Zero hunger
Openalex Percentile: Top 56%
Radiomics and Machine Learning in Medical Imaging
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Combining Genetic and Nongenetic Prognostic Factors for Colon Cancer Classification — Meng Pan, Jie Zhang · (2024) | TGRS Research Map | TGRS