ReviewCurrent cardiology reports2020
Artificial Intelligence and Texture Analysis in Cardiac Imaging.
Review in Current cardiology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.Medical & biological engineering & computing · 2025Pooled it
- The role of artificial intelligence in early detection and risk prediction of ischemic heart disease.Annals of medicine and surgery (2012) · 2026Review
- Advanced myocardial characterization and function with cardiac CT.The international journal of cardiovascular imaging · 2026Review
- Recent advances in biomarkers for cardiac fibrosis.Frontiers in cardiovascular medicine · 2026Review
- Effects of parametric feature maps on the reproducibility of radiomics from different fields of view in cardiac magnetic resonance cine images- a clinical and experimental study setting.The international journal of cardiovascular imaging · 2025Article
- Artificial intelligence in radiology and diagnostic imaging.Bioinformation · 2025Article
- Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.Medical & biological engineering & computing · 2025Article
- Advancements and applications of artificial intelligence in cardiovascular imaging: a comprehensive review.European heart journal. Imaging methods and practice · 2024Review
- ESR Bridges: CT builds bridges in coronary artery disease.European radiology · 2024Article
- Assessment of chemotherapy resistance changes in human colorectal cancer xenografts in rats based on MRI histogram features.Frontiers in oncology · 2024Article
- Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping.Arteriosclerosis, thrombosis, and vascular biology · 2023Review
- Will artificial intelligence help us in predicting outcomes in cardiac surgery?Journal of cardiac surgery · 2022Article
- Development and evaluation of a radiomics model of restingAnnals of translational medicine · 2022Article
- Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score-First Results of a Photon-Counting CT.Diagnostics (Basel, Switzerland) · 2022Article
- Machine learning cardiac-MRI features predict mortality in newly diagnosed pulmonary arterial hypertension.European heart journal. Digital health · 2022Article
- Comparison Study of Myocardial Radiomics Feature Properties on Energy-Integrating and Photon-Counting Detector CT.Diagnostics (Basel, Switzerland) · 2022Article
- Cardiac Computed Tomography Radiomics-Based Approach for the Detection of Left Ventricular Remodeling in Patients with Arterial Hypertension.Diagnostics (Basel, Switzerland) · 2022Article
- Influence of Percutaneous Drainage Surgery and the Interval to Perform Laparoscopic Cholecystectomy on Acute Cholecystitis through Genetic Algorithm-Based Contrast-Enhanced Ultrasound Imaging.Computational intelligence and neuroscience · 2022Article
- Lung Nodules in Melanoma Patients: Morphologic Criteria to Differentiate Non-Metastatic and Metastatic Lesions.Diagnostics (Basel, Switzerland) · 2021Article
- Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT.European journal of nuclear medicine and molecular imaging · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThe aim of this structured review is to summarize the current research applications and opportunities arising from artificial intelligence (AI) and texture analysis with regard to cardiac imaging. RECENT
findingsCurrent research findings suggest tremendous potential for AI in cardiac imaging, especially with regard to objective image analyses, overcoming the limitations of an observer-dependent subjective image interpretation. Researchers have used this technique across multiple imaging modalities, for instance to detect myocardial scars in cardiac MR imaging, to predict contrast enhancement in non-contrast studies, and to improve image acquisition and reconstruction. AI in medical imaging has the potential to provide novel, much-needed applications for improving patient care pertaining to the cardiovascular system. While several shortcomings are still present in the current methodology, AI may serve as a resourceful assistant to radiologists and clinicians alike.
Indexed as
Identifiers
32910325What 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.