The barriers to uptake of artificial intelligence in hepatology and how to overcome them
Artificial intelligence (AI) methods in hepatology have proliferated since the mid-2010s, with numerous publications and some regulatory approvals. Yet, adoption of AI methods in real-world clinical practice and clinical research remains limited. Despite clear benefits of using AI to analyse complex data types in hepatology, such as histopathology, radiology images, multi-omics and more recently, natural language patient data, there are still substantial barriers and challenges to its integration into routine clinical workflows. In this position paper, we assess limitations and propose a set of clear recommendations aimed at both the development of AI systems and the broader hepatology environment to facilitate the transition of AI-based diagnostic, prognostic, and predictive tools into clinical care. In particular, we argue that the use of AI in clinical trials, seamless integration into hospital information systems and building AI literacy among clinicians will ultimately drive clinical adoption. We validate this perspective through a Delphi consensus involving 34 international experts from hepatology, AI, and data science, ensuring a comprehensive and consensus-driven evaluation of our recommendations.
Authors
- Tom Luedde (ORCID: https://orcid.org/0000-0002-6288-8821)
- Debbie L. Shawcross (ORCID: https://orcid.org/0000-0001-6133-4619)
- Raquel Pérez-López (ORCID: https://orcid.org/0000-0002-9176-0130)
- Sabela Lens (ORCID: https://orcid.org/0000-0003-4900-411X)
- Eric Trépo (ORCID: https://orcid.org/0000-0003-0475-3934)
- Thomas Marjot (ORCID: https://orcid.org/0000-0002-6542-6323)
- Jan Clusmann (ORCID: https://orcid.org/0000-0003-2925-8438)
- Carolin Victoria Schneider (ORCID: https://orcid.org/0000-0002-6728-9246)
- Ashley Spann (ORCID: https://orcid.org/0000-0003-1278-7712)
- Ellis Kobina Paintsil (ORCID: https://orcid.org/0000-0001-8385-1326)
- Tobias Paul Seraphin (ORCID: https://orcid.org/0000-0001-9884-8752)
- Octavi Bassegoda
- Julien Caldéraro (ORCID: https://orcid.org/0000-0002-5370-0807)
- Jakob Nikolas Kather (ORCID: https://orcid.org/0000-0002-3730-5348)
- Stephen Gilbert (ORCID: https://orcid.org/0000-0002-1997-1689)
- Maria Balaguer‐Montero
Institutions
- Université Libre de Bruxelles (BE)
- Inserm (FR)
- King's College London (GB)
- Université Paris-Est Créteil (FR)
- Heidelberg University (DE)
- Nuffield Orthopaedic Centre (GB)
- University Hospital Heidelberg (DE)
- Düsseldorf University Hospital (DE)
- Fresenius (Germany) (DE)
- National Center for Tumor Diseases (DE)
- Hospital Clínic de Barcelona (ES)
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (ES)
- Institut Mondor de Recherche Biomédicale (FR)
- Consorci Institut D'Investigacions Biomediques August Pi I Sunyer (ES)
- University Hospital Carl Gustav Carus (DE)
- Vall d'Hebron Institute of Oncology (ES)
- Heinrich Heine University Düsseldorf (DE)
- Universitat de Barcelona (ES)
- RWTH Aachen University (DE)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Journal of Hepatology
- Published
- 2025-07-18
- DOI
- https://doi.org/10.1016/j.jhep.2025.07.003
- Citations
- 13
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 8.51
Funders
- Vanderbilt University
- Vanderbilt University Medical Center
- National Institute for Health and Care Research
- Department of Health and Social Care
- King's College London
- University of Oxford
- European Commission
- Deutscher Akademischer Austauschdienst
- Deutsche Forschungsgemeinschaft
- Institut National de la Santé et de la Recherche Médicale
- Bundesministerium für Bildung und Forschung
- Technische Universität Dresden
- Bundesministerium für Gesundheit
- Universitat de Barcelona
- Deutsche Krebshilfe
- RWTH Aachen University
- Assistance publique-Hôpitaux de Paris
- Gemeinsame Bundesausschuss
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas
- National Institutes of Health
- HORIZON EUROPE Framework Programme
- Instituto de Salud Carlos III
- Leeds Biomedical Research Centre