Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction

JHEP Reports, vol. 4, pp. 100443

Abstract

Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative and quantitative information from multiple data sources to make a diagnosis, prognosticate the disease course, and recommend a treatment. In the last 5 years, advances in artificial intelligence (AI), particularly in deep learning, have made it possible to extract clinically relevant information from complex and diverse clinical datasets. In particular, histopathology and radiology image data contain diagnostic, prognostic and predictive information which AI can extract. Ultimately, such AI systems could be implemented in clinical routine as decision support tools. However, in the context of hepatology, this requires further large-scale clinical validation and regulatory approval. Herein, we summarise the state of the art in AI in hepatology with a particular focus on histopathology and radiology data. We present a roadmap for the further development of novel biomarkers in hepatology and outline critical obstacles which need to be overcome.

Authors 4

1. Julius Chapiro

   Yale University

   Affiliation as printed

   Section of Interventional Radiology, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA

2. Valérie Paradis

   Inserm · Université Paris Cité · Hôpital Beaujon · Assistance Publique – Hôpitaux de Paris · Centre de Recherche sur l'Inflammation

   Affiliation as printed

   INSERM U1149 "Centre de Recherche Sur L'inflammation", CRI, Université de Paris, Paris, France

   University Paris, AP-HP, Department of Pathology, Hôpital Beaujon, Clichy, France

3. Tobias Paul Seraphin Aachen Department of Medicine III

   Düsseldorf University Hospital · Universitätsklinikum Aachen · Heinrich Heine University Düsseldorf · RWTH Aachen University

   Affiliation as printed

   Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty of Heinrich Heine University Düsseldorf, University Hospital Düsseldorf, Düsseldorf, Germany

   Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany

4. Jakob Nikolas Kather corresponding Aachen Department of Medicine III

   University of Leeds · University Hospital Heidelberg · National Center for Tumor Diseases · Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany

   Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany

   Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK