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Machine Learning Model Integrating Clinical Features, CT Radiomics, and Transfer Learning for Predicting Aggressive Recurrence of Hepatocellular Carcinoma

2026-08-25

Abstract excerpt

<title>Abstract</title> <p>Objective To predict aggressive recurrence of hepatocellular carcinoma (HCC) after curative resection, this study aimed to develop a preoperative noninvasive prediction model by integrating clinical features, radiomics, and transfer learning–based deep features, thereby enabling early identification of high-risk patients and providing a reference for individualized perioperative treatm...

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Literature Corpus work
eadf194e-ab98-5755-b2d6-6d971e2e6635
DOI
10.21203/rs.3.rs-10555359/v1
Open publication

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Machine Learning Model Integrating Clinical Features, CT Radiomics, and Transfer Learning for Predicting Aggressive Recurrence of Hepatocellular CarcinomaDOI 10.21203/rs.3.rs-10555359/v1
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