Feasibility of machine learning-based modeling and prediction using multiple centers data to assess intrahepatic cholangiocarcinoma outcomes

BACKGROUND AND AIMS: Currently, there are still no definitive consensus in the treatment of intrahepatic cholangiocarcinoma (iCCA). This study aimed to build a clinical decision support tool based on machine learning using the Surveillance, Epidemiology, and End Results (SEER) database and the data...

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Detalles Bibliográficos
Autores principales: Zhou, Shuang-Nan, Jv, Da-Wei, Meng, Xiang-Fei, Zhang, Jing-Jing, Liu, Chun, Wu, Ze-Yi, Hong, Na, Lu, Yin-Ying, Zhang, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Gastroenterology & Hepatology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9809369/
https://www.ncbi.nlm.nih.gov/pubmed/36576390
http://dx.doi.org/10.1080/07853890.2022.2160008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9809369/
https://www.ncbi.nlm.nih.gov/pubmed/36576390
http://dx.doi.org/10.1080/07853890.2022.2160008

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