ReviewTexas Heart Institute journal2022
Artificial Intelligence for Education, Proctoring, and Credentialing in Cardiovascular Medicine.
Review in Texas Heart Institute journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Performance of 5 Large Language Models in Perioperative Consultation for Pediatric Hypospadias: Cross-Sectional Comparative Study.Journal of medical Internet research · 2026Article
- A perspective on improving the teaching quality of aerospace cardiovascular medicine courses.Frontiers in medicine · 2026Article
- Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.BMC medical informatics and decision making · 2024Review
- Impact of artificial intelligence on the training of general surgeons of the future: a scoping review of the advances and challenges.Acta cirurgica brasileira · 2024Article
- Review
- The power of visuals: taking patient education to the next level.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023Article
- Bioinformatics-based and multiscale convolutional neural network screening of herbal medicines for improving the prognosis of liver cancer: a novel approach.Frontiers in medicine · 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence and machine learning are rapidly gaining popularity in every aspect of cardiovascular medicine. This review discusses the past, present, and future of artificial intelligence in education, remote proctoring, credentialing, research, and publication as they pertain to cardiovascular procedures. This review describes the benefits and limitations of artificial intelligence and machine learning and the exciting potential of integrating advanced simulation, holography, virtual reality, and extended reality into disease diagnosis and patient care, as well as their roles in cardiovascular research and education. Nonetheless, much of the available data resides in electronic medical records or within industry-sponsored proprietary programs that are not compatible or standardized for current clinical application. Many areas in cardiovascular medicine would benefit from the introduction or increased use of artificial intelligence. Web-based artificial intelligence applications could be used to address unmet needs for education, on-demand procedural proctoring, credentialing, and recredentialing for interventionists and physicians in remote locations. Further progress in artificial intelligence will require further collaboration among computer scientists and researchers in order to identify and correct the most relevant problems and to implement the best data-based approach to achieving this goal. The future success of artificial intelligence in cardiovascular medicine will depend on the degree of collaboration between all pertinent experts in this field. This will undoubtedly be a prolonged, stepwise process.
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.