ReviewCardiology research and practice2020
Artificial Intelligence (AI) and Cardiovascular Diseases: An Unexpected Alliance.
Review in Cardiology research and practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses 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
31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 98 citations in OpenAlex.
- Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems.Current cardiology reviews · 2025Pooled it
- E-Cardiac Care: A Comprehensive Systematic Literature Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Cardiovascular Diseases: Exploring Epidemiology, Pathophysiology, Risk Factors, and Medicinal Plant-Based Therapies: A Narrative Review.Health science reports · 2026Article
- Artificial intelligence in cardiology: an updated systematic review with ethical considerations and challenges in implementing artificial intelligence models.Annals of medicine and surgery (2012) · 2026Article
- Digital health interventions for urinary tract infection prevention and management in people living with dementia and their family caregivers: a scoping review.The Gerontologist · 2026Article
- Mini- and Micro-Invasive Approaches in Cardiac Surgery: Current Techniques, Outcomes, and Future Perspectives.Medicina (Kaunas, Lithuania) · 2026Review
- The use and the cost of inpatient diagnostic and therapeutic procedures for cardiovascular diseases in public hospitals of Isfahan, Iran.ARYA atherosclerosis · 2026Article
- Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review.Journal of the American Heart Association · 2025Review
- Review
- Non-invasive Assessment of Coronary Artery Disease: The Role of AI in the Current Status and Future Directions.Cureus · 2025Review
- Application of artificial intelligence in osteoporosis: a review.Frontiers in medicine · 2025Review
- Review
- Review on Emerging Therapeutic Strategies for Managing Cardiovascular Disease.Current cardiology reviews · 2024Review
- Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review.Heliyon · 2023Review
- A New Cardiovascular Mock Loop Driven by Novel Active Capacitance in Normal and Abnormal Conditions.Applied bionics and biomechanics · 2023Article
- Short-term anti-remodeling effects of gliflozins in diabetic patients with heart failure and reduced ejection fraction: an explainable artificial intelligence approach.Frontiers in pharmacology · 2023Article
- Article
- Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.PLOS digital health · 2023Article
- Clinical Modelling of RVHF Using Pre-Operative Variables: A Direct and Inverse Feature Extraction Technique.Diagnostics (Basel, Switzerland) · 2022Article
- Development of an Artificial Neural Network for the Detection of Supporting Hindlimb Lameness: A Pilot Study in Working Dogs.Animals : an open access journal from MDPI · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular disease (CVD), despite the significant advances in the diagnosis and treatments, still represents the leading cause of morbidity and mortality worldwide. In order to improve and optimize CVD outcomes, artificial intelligence techniques have the potential to radically change the way we practice cardiology, especially in imaging, offering us novel tools to interpret data and make clinical decisions. AI techniques such as machine learning and deep learning can also improve medical knowledge due to the increase of the volume and complexity of the data, unlocking clinically relevant information. Likewise, the use of emerging communication and information technologies is becoming pivotal to create a pervasive healthcare service through which elderly and chronic disease patients can receive medical care at their home, reducing hospitalizations and improving quality of life. The aim of this review is to describe the contemporary state of artificial intelligence and digital health applied to cardiovascular medicine as well as to provide physicians with their potential not only in cardiac imaging but most of all in clinical practice.
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.