ReviewLa Radiologia medica2023
Clinical applications of artificial intelligence in liver imaging.
Review in La Radiologia medica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis 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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Role of radiomics in staging liver fibrosis: a meta-analysis.BMC medical imaging · 2024Pooled it
- Hyperpolarized MRI in Oncology-A Review of Clinical Studies and Evaluation of Preclinical Liver Studies.NMR in biomedicine · 2026Review
- Predicting the prognosis of hepatocellular carcinoma after curative resection using a nomogram based on the ratio of prealbumin to platelet distribution width.Journal of gastrointestinal oncology · 2025Article
- Artificial Intelligence Applications in Interventional Radiology.Journal of personalized medicine · 2025Review
- Evaluation of AI diagnostic systems for breast ultrasound: comparative analysis with radiologists and the effect of AI assistance.Japanese journal of radiology · 2025Article
- The Evolution and Clinical Impact of Deep Learning Technologies in Breast MRI.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Colorectal cancer liver metastases: A radiologic point of view.World journal of gastrointestinal oncology · 2025Article
- Radiomics Beyond Radiology: Literature Review on Prediction of Future Liver Remnant Volume and Function Before Hepatic Surgery.Journal of clinical medicine · 2025Review
- Dynamic changes of radiological and radiomics patterns based on MRI in viable hepatocellular carcinoma after transarterial chemoembolization.Abdominal radiology (New York) · 2025Article
- JJR-TOP GUN Phase 1, Year 2: new perspectives through the integration of artificial intelligence and radiology.Japanese journal of radiology · 2025Article
- Contrast-enhanced thin-slice abdominal CT with super-resolution deep learning reconstruction technique: evaluation of image quality and visibility of anatomical structures.Japanese journal of radiology · 2025Article
- Advancing clinical MRI exams with artificial intelligence: Japan's contributions and future prospects.Japanese journal of radiology · 2025Review
- Applications of artificial intelligence in interventional oncology: An up-to-date review of the literature.Japanese journal of radiology · 2025Review
- Review
- MRI management of focal liver lesions: what a beginner cannot fail to know.Frontiers in oncology · 2025Review
- Artificial intelligence in radiology and diagnostic imaging.Bioinformation · 2025Article
- Article
- Percutaneous microwave ablation of HCC: comparison between 100 and 150 W technology systems.La Radiologia medica · 2024Article
- A review of deep learning approaches for multimodal image segmentation of liver cancer.Journal of applied clinical medical physics · 2024Review
- Radiomics and 256-slice-dual-energy CT in the automated diagnosis of mild acute pancreatitis: the innovation of formal methods and high-resolution CT.La Radiologia medica · 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
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review outlines the current status and challenges of the clinical applications of artificial intelligence in liver imaging using computed tomography or magnetic resonance imaging based on a topic analysis of PubMed search results using latent Dirichlet allocation. LDA revealed that "segmentation," "hepatocellular carcinoma and radiomics," "metastasis," "fibrosis," and "reconstruction" were current main topic keywords. Automatic liver segmentation technology using deep learning is beginning to assume new clinical significance as part of whole-body composition analysis. It has also been applied to the screening of large populations and the acquisition of training data for machine learning models and has resulted in the development of imaging biomarkers that have a significant impact on important clinical issues, such as the estimation of liver fibrosis, recurrence, and prognosis of malignant tumors. Deep learning reconstruction is expanding as a new technological clinical application of artificial intelligence and has shown results in reducing contrast and radiation doses. However, there is much missing evidence, such as external validation of machine learning models and the evaluation of the diagnostic performance of specific diseases using deep learning reconstruction, suggesting that the clinical application of these technologies is still in development.
Indexed as
Identifiers
37165151What 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.