Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

By combining multiparameter magnetic resonance imaging with the effectiveness and robustness of ML-based predictive models, the proposed clinical RFM can serve as an insight tool for preoperative assessment of MLM risk stratification and provide important information for individual diagnosis and treatment of rectal cancer patients.

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Publication Details

Journal
World Journal of Gastrointestinal Oncology
Published
2024-12-11
DOI
https://doi.org/10.4251/wjgo.v17.i1.96598
Citations
6
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
2.43
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article

Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

Zhi‐Da Long, Zhi-Xiang Xing, Yu Xiao, Rui Wang
6 citations
World Journal of Gastrointestinal Oncology
Radiomics and Machine Learning in Medical Imaging
2.43
article

Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

Zhi‐Da Long, Zhi-Xiang Xing, Yu Xiao, Rui Wang
article en
6 citations

Abstract

By combining multiparameter magnetic resonance imaging with the effectiveness and robustness of ML-based predictive models, the proposed clinical RFM can serve as an insight tool for preoperative assessment of MLM risk stratification and provide important information for individual diagnosis and treatment of rectal cancer patients.

World Journal of Gastrointestinal OncologyVol. 17(1)
Yangtze University (CN)
Reduced inequalities
Openalex Percentile: Top 10%
Radiomics and Machine Learning in Medical Imaging
2.43
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