ReviewNetherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation2019
Artificial intelligence in cardiovascular imaging: state of the art and implications for the imaging cardiologist.
Review in Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
- Review
- Precision Cardio-Oncology and Nuclear Imaging: Current Applications, Molecular Innovations, and Future Trajectories.Cancers · 2026Review
- Deep Learning for Cardiac Wall Motion Analysis: A Review of Methods, Challenges, and Clinical Applications.Annals of biomedical engineering · 2026Review
- Review
- Insights Into the Future: Assessing Medical Students' Artificial Intelligence Readiness - A Cross-Sectional Study at Kerman University of Medical Sciences (2022).Health science reports · 2025Article
- Bibliometric analysis of artificial intelligence applications in cardiovascular imaging: trends, impact, and emerging research areas.Annals of medicine and surgery (2012) · 2025Article
- Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward.BMC medical education · 2025Article
- Cardiovascular evaluation of athletes ahead of participation.Frontiers in cardiovascular medicine · 2025Article
- Precision cardiovascular medicine: shifting the innovation paradigm.Frontiers in science · 2025Article
- Review
- The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis.Cureus · 2024Review
- Computer-aided analysis of radiological images for cancer diagnosis: performance analysis on benchmark datasets, challenges, and directions.EJNMMI reports · 2024Review
- Determining medical students' anxiety and readiness levels about artificial intelligence.Heliyon · 2024Article
- Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes.Diagnostics (Basel, Switzerland) · 2024Review
- Healthcare students' knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam.Heliyon · 2023Article
- The Nottingham Ischaemic Cardiovascular Magnetic Resonance resource (NotIs CMR): a prospective paired clinical and imaging scar database-protocol.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2023Article
- Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study.Scientific reports · 2023Article
- Psychometric evaluation of Persian version of medical artificial intelligence readiness scale for medical students.BMC medical education · 2023Article
- Artificial Intelligence Applications in Cardiovascular Magnetic Resonance Imaging: Are We on the Path to Avoiding the Administration of Contrast Media?Diagnostics (Basel, Switzerland) · 2023Review
- Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.PLOS digital health · 2023Article
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
Abstract
Healthcare, conceivably more than any other area of human endeavour, has the greatest potential to be affected by artificial intelligence (AI). This potential has been shown by several reports that demonstrate equal or superhuman performance in medical tasks that aim to improve efficiency, diagnosis and prognosis. This review focuses on the state of the art of AI applications in cardiovascular imaging. It provides an overview of the current applications and studies performed, including the potential value, implications, limitations and future directions of AI in cardiovascular imaging.It is envisioned that AI will dramatically change the way doctors practise medicine. In the short term, it will assist physicians with easy tasks, such as automating measurements, making predictions based on big data, and putting clinical findings into an evidence-based context. In the long term, AI will not only assist doctors, it has the potential to significantly improve access to health and well-being data for patients and their caretakers. This empowers patients. From a physician's perspective, reliable AI assistance will be available to support clinical decision-making. Although cardiovascular studies implementing AI are increasing in number, the applications have only just started to penetrate contemporary clinical care.
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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.