ArticleEuropean radiology2021
Feasibility and prognostic role of machine learning-based FFR
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed, 33 citations in OpenAlex.
- Combined prognostic value of AI-derived CT-FFR and high-risk plaque characteristics in patients with newly diagnosed chronic coronary syndrome: a prospective cohort study.Frontiers in cardiovascular medicine · 2025Trial
- Feasibility of On-Site CT-FFR Analysis in Ruling Out In-Stent Restenosis on Cardiac PCCT.Journal of cardiovascular development and disease · 2026Article
- Clinical use of coronary computed tomography angiography-derived fractional flow reserve: expert consensus by an International Working Group.European radiology · 2026Article
- FFR-CT: Technical Advances and Implementation in Clinical Practice.Journal of imaging · 2026Review
- CCTA-derived trans-lesion fractional flow reserve gradient for predicting cardiovascular events after PCI: a prospective observational study.BMC medical imaging · 2026Observational
- Artificial intelligence in cardiology in the current era: a narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Article
- Cardiac Computed Tomography: Technological Developments and Clinical Applications.Journal of cardiovascular development and disease · 2025Review
- Machine learning based model for predicting cardiovascular disease using dynamic triglyceride-glucose index: a longitudinal study cohort CHARLS database.Journal of geriatric cardiology : JGC · 2025Article
- Computed Tomography and Coronary Plaque Analysis.Tomography (Ann Arbor, Mich.) · 2025Review
- Clinical Applications of Fractional Flow Reserve Derived from Computed Tomography in Coronary Artery Disease.Mayo Clinic proceedings. Digital health · 2025Review
- Diagnostic value of deep learning reconstruction-based subtraction CT-FFR in patients with calcified-related stenosis or stent implantation.Quantitative imaging in medicine and surgery · 2025Article
- Artificial Intelligence based fractional flow reserve.Cardiology journal · 2025Review
- Patient Management Following Percutaneous Coronary Intervention.JACC. Advances · 2025Review
- A Machine Learning Model Integrating Tongue Image Features and Myocardial Injury Markers Predicts Major Adverse Cardiovascular Events in Patients with Coronary Heart Disease.International journal of general medicine · 2025Article
- Predictive Value of CT Fractional Flow Reserve and Fat Attenuation Index Derived from Coronary CT Angiography for In-Stent Restenosis After Percutaneous Coronary Intervention.Therapeutics and clinical risk management · 2025Article
- Prognostic Value Of Deep Learning Based RCA PCAT and Plaque Volume Beyond CT-FFR In Patients With Stent ImplantationCurrent medical imaging · 2025Article
- Prognostic Value of Coronary CT Angiography-Derived Quantitative Flow Ratio in Suspected Coronary Artery Disease.Radiology · 2024Article
- Stent-specific fat attenuation index is associated with target vessel revascularization after PCI.European radiology · 2024Article
- CT-derived Fractional Flow Reserve: How, When, and Where to use this Novel Cardiac Imaging Tool.Current cardiology reviews · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivesTo investigate the feasibility and prognostic implications of coronary CT angiography (CCTA) derived fractional flow reserve (FFR
methodsFirstly, the feasibility of FFR
resultsPer-patient accuracy of FFR
conclusionsNoninvasive ML-based FFR KEY POINTS: • Machine-learning-based FFR
Indexed as
Identifiers
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.