ReviewJournal of clinical and translational hepatology2023
Current Status and Analysis of Machine Learning in Hepatocellular Carcinoma.
Review in Journal of clinical and translational hepatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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
23 citing papers in PubMed.
- Computed tomography radiomics-based machine learning nomogram for preoperative prediction of glypican-3 expression in hepatocellular carcinoma.World journal of radiology · 2026Article
- [APASL clinical practice guidelines on the management of chronic hepatitis B infection: a 2026 update].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026Article
- APASL clinical practice guidelines on the management of chronic hepatitis B infection: a 2026 update.Hepatology international · 2026Article
- Machine learning outperforms large language models for survival prediction in advanced hepatocellular carcinoma: a multicenter study.Scientific reports · 2026Article
- Predicting Response to Transarterial Chemoembolization in Hepatocellular Carcinoma Using Machine Learning Models.The Indian journal of radiology & imaging · 2026Article
- Pioneering efficient deep learning architectures for enhanced hepatocellular carcinoma prediction and clinical translation.World journal of gastrointestinal oncology · 2026Article
- Advances and Emerging Techniques in Transarterial Chemoembolization for Hepatocellular Carcinoma.Cancers · 2026Review
- Big Data Analytics in Large Cohorts: Opportunities and Challenges for Research in Hepatology.Seminars in liver disease · 2025Review
- Multiple machine learning algorithms identified SLC6A8 as a diagnostic biomarker of the late stage of Hepatocellular carcinoma.Discover oncology · 2025Article
- Plasma lipidomic analysis reveals disruption of ether phosphatidylcholine biosynthesis and facilitates early detection of hepatitis B-related hepatocellular carcinoma.Lipids in health and disease · 2025Article
- Current and new strategies for hepatocellular carcinoma surveillance.Gastroenterology report · 2025Review
- Research progress of artificial intelligence and machine learning in pulmonary embolism.Frontiers in medicine · 2025Review
- Construction and Validation of a T Cell Exhaustion-Related Prognostic Signature in Cholangiocarcinoma.International journal of genomics · 2025Article
- Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma.Cancer informatics · 2025Review
- Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.European journal of medical research · 2024Article
- Article
- Machine Learning Algorithm for Predicting Distant Metastasis of T1 and T2 Gallbladder Cancer Based on SEER Database.Bioengineering (Basel, Switzerland) · 2024Article
- Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.Scientific reports · 2024Article
- Radiomics and machine learning based on preoperative MRI for predicting extrahepatic metastasis in hepatocellular carcinoma patients treated with transarterial chemoembolization.European journal of radiology open · 2024Article
- From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring.World journal of gastroenterology · 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is a common tumor. Although the diagnosis and treatment of HCC have made great progress, the overall prognosis remains poor. As the core component of artificial intelligence, machine learning (ML) has developed rapidly in the past decade. In particular, ML has become widely used in the medical field, and it has helped in the diagnosis and treatment of cancer. Different algorithms of ML have different roles in diagnosis, treatment, and prognosis. This article reviews recent research, explains the application of different ML models in HCC, and provides suggestions for follow-up research.
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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.