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