Evaluation of the role of comedication properties in the severity of drug-induced liver injury using machine learning techniques
These findings offer valuable insights into predicting the severity of DILI. By identifying the key factors that influence the severity of DILI, it would be possible for healthcare providers to predict the severity of damage in a patient with DILI. This enables early interventions in cases of DILI, thus subsequently reducing its negative effects.
Authors
- Ismael Álvarez‐Álvarez (ORCID: https://orcid.org/0000-0001-6271-0604)
- Mercedes Robles‐Díaz (ORCID: https://orcid.org/0000-0002-2365-2787)
- A. González-Jiménez (ORCID: https://orcid.org/0000-0002-7059-1577)
- Raúl J. Andrade (ORCID: https://orcid.org/0000-0002-1565-0757)
- Minjun Chen (ORCID: https://orcid.org/0000-0002-6453-2351)
- Camilla Stephens (ORCID: https://orcid.org/0000-0002-0796-9610)
- M. Isabel Lucena (ORCID: https://orcid.org/0000-0001-9586-4896)
- Inmaculada Medina‐Cáliz (ORCID: https://orcid.org/0000-0003-0471-6658)
- Hao Niu (ORCID: https://orcid.org/0009-0007-3813-6586)
- Irene Victoria Bermúdez-Pérez
Institutions
- United States Food and Drug Administration (US)
- University Hospital Schleswig-Holstein (DE)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (ES)
- Food and Drug Administration (TH)
- Instituto de Investigación Biomédica de Málaga (ES)
- Universidad de Málaga (ES)
- University of Lübeck (DE)
Publication Details
- Journal
- Expert Opinion on Drug Metabolism & Toxicology
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1080/17425255.2025.2525470
- Citations
- 1
- Primary Topic
- Drug-Induced Hepatotoxicity and Protection
- Type
- article
- Field-Weighted Citation Impact
- 1.56