Machine learning-based normal tissue complication probability model for predicting albumin-bilirubin (ALBI) grade increase in hepatocellular carcinoma patients

PURPOSE: The aim of this study was to develop a normal tissue complication probability model using a machine learning approach (ML-based NTCP) to predict the risk of radiation-induced liver disease in hepatocellular carcinoma (HCC) patients. MATERIALS AND METHODS: The study population included 201 H...

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Detalles Bibliográficos
Autores principales: Prayongrat, Anussara, Srimaneekarn, Natchalee, Thonglert, Kanokporn, Khorprasert, Chonlakiet, Amornwichet, Napapat, Alisanant, Petch, Shirato, Hiroki, Kobashi, Keiji, Sriswasdi, Sira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730671/
https://www.ncbi.nlm.nih.gov/pubmed/36476512
http://dx.doi.org/10.1186/s13014-022-02138-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730671/
https://www.ncbi.nlm.nih.gov/pubmed/36476512
http://dx.doi.org/10.1186/s13014-022-02138-8

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