PHENO-RAG: An artificial intelligence tool for guideline-informed management decisions in hepatocellular carcinoma

Background & Aims: Management of hepatocellular carcinoma (HCC) poses unique challenges due to its development in the context of chronic liver disease and the availability of multiple treatment options. Although multidisciplinary team (MDT) management improves outcomes, universal MDT discussion...

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Бібліографічні деталі
Автори:	Ciro Celsa, Mauro Giuffrè, Gabriele Di Maria, Salvatore Gruttadauria, Ugo Palazzo, Roberto Miraglia, Luigi Maruzzelli, Duilio Pagano, Roberto Cannella, Federico Midiri, Roberta Ciccia, Mauro Salvato, Alessandro Grova, Sofia Rao, Gaetano Giusino, Alessio Quartararo, Guido Cusimano, Alba Sparacino, Valeria Gaudioso, Valeria Genovese, Rosangela Montenegro, Claudia La Mantia, Francesco Mercurio, Simone Kresevic, Milos Ajcevic, Giuseppe Cabibbo, Giansalvo Cirrincione, Calogero Cammà
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Elsevier 2026-04-01
Серія:	JHEP Reports
Предмети:	Large Language Models Hepatocellular carcinoma Retrieval Augmented Generation Clinical Decision Support Patient Phenotyping
Онлайн доступ:	http://www.sciencedirect.com/science/article/pii/S2589555925003982
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PHENO-RAG: An artificial intelligence tool for guideline-informed management decisions in hepatocellular carcinoma

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