Machine Learning‐Based Model for Predicting Recurrence‐Free Survival After Interventional Therapy in Malnourished Hepatocellular Carcinoma Patients

We developed a nomogram that can predict the 1-, 3-, and 5-year RFS of malnourished HCC patients after undergoing the combination treatment; the constructed nomogram exhibited favorable predictive capabilities.

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Publication Details

Journal
Cancer Medicine
Published
2025-09-01
DOI
https://doi.org/10.1002/cam4.71157
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine Learning‐Based Model for Predicting Recurrence‐Free Survival After Interventional Therapy in Malnourished Hepatocellular Carcinoma Patients

Chunwang Yuan, Bin Sun, Yonghong Zhang, Ningning Lu et al.
Cancer Medicine
Hepatocellular Carcinoma Treatment and Prognosis
article

Machine Learning‐Based Model for Predicting Recurrence‐Free Survival After Interventional Therapy in Malnourished Hepatocellular Carcinoma Patients

Chunwang Yuan, Bin Sun, Yonghong Zhang, Ningning Lu, Xiongwei Cui, Wenfeng Gao
article en

Abstract

We developed a nomogram that can predict the 1-, 3-, and 5-year RFS of malnourished HCC patients after undergoing the combination treatment; the constructed nomogram exhibited favorable predictive capabilities.

Cancer MedicineVol. 14(18)
Beijing YouAn Hospital (CN)
Openalex Percentile: Top 67%
Hepatocellular Carcinoma Treatment and Prognosis
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