2026-05-28T14:24:37Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/381642026-02-03T11:02:50Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Niu, Hao author Álvarez-Álvarez, Ismael author Chen, Minjun author 2025-02-21 Drug-induced liver injury (DILI) is a complex and potentially severe adverse reaction to drugs, herbal products or dietary supplements. DILI can mimic other liver diseases clinical presentation, and currently lacks specific diagnostic biomarkers, which hinders its diagnosis. In some cases, DILI may progress to acute liver failure. Given its public health risk, novel methodologies to enhance the understanding of DILI are crucial. Recently, the increasing availability of larger datasets has highlighted artificial intelligence (AI) as a powerful tool to construct complex models. In this review, we summarise the evidence about the use of AI in DILI research, explaining fundamental AI concepts and its subfields. We present findings from AI-based approaches in DILI investigations for risk stratification, prognostic evaluation and causality assessment and discuss the adoption of natural language processing (NLP) and large language models (LLM) in the clinical setting. Finally, we explore future perspectives and challenges in utilising AI for DILI research. Niu H, Alvarez-Alvarez I, Chen M. Artificial Intelligence: An Emerging Tool for Studying Drug-Induced Liver Injury. Liver Int. 2025;45(3):e70038 https://hdl.handle.net/10630/38164 10.1111/liv.70038 Inteligencia artificial en medicina Proceso en lenguaje natural (Informática) Hígado - Efectos de los medicamentos Hígado - Enfermedades Aprendizaje automático (Inteligencia artificial) Hepatotoxicidad Artificial Intelligence: an emerging tool for studying drug-induced liver injury.