2023
DOI: 10.21203/rs.3.rs-3320033/v1
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Machine learning-based radiomic models for predicting metachronous liver metastases in colorectal cancer patients: a multimodal study

Jian-Ping Wang,
Ze-Ning Zhang,
Ding-Bo Shu
et al.

Abstract: Purpose The purpose of this study was to investigate whether a multimodal radiomic model powered by machine learning (ML) can accurately predict the occurrence of metachronous liver metastases (MLM) in patients with colorectal cancer (CRC). Patients and methods: A total of 157 consecutive patients with CRC between 2010 and 2020 were retrospectively included. Out of these patients, 67 experienced liver metastases within 2 years of treatment, while the remaining patients did not. Radiomic features were extract… Show more

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