ReviewJHEP reports : innovation in hepatology2024
Use of artificial intelligence for liver diseases: A survey from the EASL congress 2024.
Review in JHEP reports : innovation in hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Response evaluation to systemic therapy in HCC: Current challenges and future perspectives.Hepatology (Baltimore, Md.) · 2026Review
- Impact of Transjugular Intrahepatic Portosystemic Shunt on Waitlist and Post-transplant Outcomes in Liver Transplant Candidates.Digestive diseases and sciences · 2026Article
- Machine Learning Predicts Hepatocellular Carcinoma Risk from Routine Clinical Data: A Large Population-Based Multicentric Study.Cancer discovery · 2026Article
- Evolving B-mode ultrasound-based techniques for assessing metabolic dysfunction-associated steatotic liver disease: Now and beyond.Liver research (Beijing, China) · 2026Review
- Ahead, a Novel Validated Machine Learning Model for Clinical Diagnosis of Alcohol Associated Hepatitis.Research square · 2026Article
- MASLD Management in Spain: A Nationwide Survey of Gastroenterologists Highlighting Gaps in Risk Assessment and Primary Care Coordination.Journal of clinical medicine · 2026Article
- Artificial intelligence and digital transformation of gastroenterology and hepatology: A critical review of clinical applications and future challenges.World journal of hepatology · 2026Review
- Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.Gut and liver · 2026Review
- Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: Transforming diagnosis and therapeutic approaches.World journal of gastroenterology · 2026Review
- [Research progress and future prospects for artificial intelligence in the diagnosis and treatment of fatty liver disease].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025Review
- Evaluating large language models' performance in answering common questions on drug-induced liver injury.JHEP reports : innovation in hepatology · 2025Article
- [Surgical management of giant hemangiomas in the caudate lobe: an overview on the intraoperative management and role of artificial intelligence (AI) in improvement of the surgical results].Chirurgie (Heidelberg, Germany) · 2025Article
- Immunopathogenic mechanisms and immunoregulatory therapies in MASLD.Cellular & molecular immunology · 2025Review
- Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells.Cellular & molecular immunology · 2025Review
- Review
- MASLD Under the Microscope: How microRNAs and Microbiota Shape Hepatic Metabolic Disease Progression.International journal of molecular sciences · 2025Review
- Big Data Analytics in Large Cohorts: Opportunities and Challenges for Research in Hepatology.Seminars in liver disease · 2025Review
- ASS1 is a hub gene and possible therapeutic target for regulating metabolic dysfunction-associated steatotic liver disease modulated by a carbohydrate-restricted diet.Molecular diversity · 2025Article
- Gut Microbiome-Liver-Brain axis in Alcohol Use Disorder. The role of gut dysbiosis and stress in alcohol-related cognitive impairment progression: possible therapeutic approaches.Neurobiology of stress · 2025Article
- Advancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease-Applications and Challenges in Personalized Care.Bioengineering (Basel, Switzerland) · 2024Review
Corrections and comments
- Erratum issued
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) methods enable humans to analyse large amounts of data, which would otherwise not be feasibly quantifiable. This is especially true for unstructured visual and textual data, which can contain invaluable insights into disease. The hepatology research landscape is complex and has generated large amounts of data to be mined. Many open questions can potentially be addressed with existing data through AI methods. However, the field of AI is sometimes obscured by hype cycles and imprecise terminologies. This can conceal the fact that numerous hepatology research groups already use AI methods in their scientific studies. In this review article, we aim to assess the contemporaneous use of AI methods in hepatology in Europe. To achieve this, we systematically surveyed all scientific contributions presented at the EASL Congress 2024. Out of 1,857 accepted abstracts (1,712 posters and 145 oral presentations), 6 presentations (∼4%) and 69 posters (∼4%) utilised AI methods. Of these, 55 posters were included in this review, while the others were excluded due to missing posters or incomplete methodologies. Finally, we summarise current academic trends in the use of AI methods and outline future directions, providing guidance for scientific stakeholders in the field of hepatology.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.