Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases

Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases

Objectives: This study explored the clinical utility of CT radiomics-driven machine learning as a predictive marker for chemotherapy response in colorectal liver metastasis (CRLM) patients. Methods: We included 150 CRLM patients who underwent first-line doublet chemotherapy, dividing them into a tra...

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Bibliographic Details
Main Authors: Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba
Format: Article
Language:English
Published: The Japan Society of Coloproctology 2025-01-01
Series:Journal of the Anus, Rectum and Colon
Subjects:
machine learning
ct texture analysis
colorectal cancer
liver metastases
chemotherapy
Online Access:https://www.jstage.jst.go.jp/article/jarc/9/1/9_2024-077/_pdf/-char/en
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https://www.jstage.jst.go.jp/article/jarc/9/1/9_2024-077/_pdf/-char/en

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