ArticleUltrasonography (Seoul, Korea)2023
Artificial intelligence models for the diagnosis and management of liver diseases.
Article in Ultrasonography (Seoul, Korea), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
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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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic accuracy of computer-aided detection for colorectal polyps of any size, ≤ 5 mm, and 6-9 mm: a meta-analysis.World journal of surgical oncology · 2026Pooled it
- Convergence of disciplines: a systematic review of multidisciplinary development approaches in artificial intelligence.Frontiers in digital health · 2025Pooled it
- Large Language Models for Heterogeneous Data Mining in Liver Disease: Framework Development and Retrospective Validation Study.Journal of medical Internet research · 2026Article
- Evolving B-mode ultrasound-based techniques for assessing metabolic dysfunction-associated steatotic liver disease: Now and beyond.Liver research (Beijing, China) · 2026Review
- An efficient pyramid scene parsing network with multi-scale feature fusion for liver segmentation in magnetic resonance imaging.Frontiers in medicine · 2026Article
- The role of artificial intelligence in gastroenterology: current perspectives and future directions-narrative review.Translational gastroenterology and hepatology · 2026Review
- Review
- AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022.BMC medical education · 2025Article
- Enhancing ultrasonographic detection of hepatocellular carcinoma with artificial intelligence: current applications, challenges and future directions.BMJ open gastroenterology · 2025Review
- Advancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease-Applications and Challenges in Personalized Care.Bioengineering (Basel, Switzerland) · 2024Review
- Physiological network approach to prognosis in cirrhosis: A shifting paradigm.Physiological reports · 2024Review
- Hybrid Quantum Image Classification and Federated Learning for Hepatic Steatosis Diagnosis.Diagnostics (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
With the development of more advanced methods for the diagnosis and treatment of diseases, the data required for medical care are becoming complex, and misinterpretation of information due to human error may result in serious consequences. Human error can be avoided with the support of artificial intelligence (AI). AI models trained with various medical data for diagnosis and management of liver diseases have been applied to hepatitis, fatty liver disease, liver cirrhosis, and liver cancer. Some of these models have been reported to outperform human experts in terms of performance, indicating their potential for supporting clinical practice given their high-speed output. This paper summarizes the recent advances in AI for liver disease and introduces the AI-aided diagnosis of liver tumors using B-mode ultrasonography.
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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.