ReviewCurrent atherosclerosis reports2024
Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?
Review in Current atherosclerosis reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Effectiveness of Digital Interventions to Increase Preventive Care Uptake in Older Adults: Systematic Review.JMIR aging · 2026Pooled it
- Digital Health Solutions for Cardiovascular Disease Prevention: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Artificial Intelligence in Cardiovascular Risk Prediction: An Up-to-Date Narrative Review on the Emerging Role of Lipid Profile-Based Models.Journal of clinical medicine · 2026Review
- Personalized prevention for all: changing how we approach the future of prevention.Health affairs scholar · 2026Article
- Digital Educational Strategies to Implement Evidence-Based Care for Atherosclerotic Cardiovascular Disease.Current atherosclerosis reports · 2026Review
- Large Language Models in Cardiovascular Prevention: A Narrative Review and Governance Framework.Diagnostics (Basel, Switzerland) · 2026Review
- Precision medicine and personalized nursing in cardiovascular disease: clinical applications and frontier developments.Frontiers in cardiovascular medicine · 2026Review
- Cardiovascular Prevention: Current Gaps and Future Directions.Diagnostics (Basel, Switzerland) · 2025Review
- Pre-trained Artificial Intelligence Models in the Prediction and Classification of Atherosclerotic Cardiovascular Disease.The Eurasian journal of medicine · 2025Article
- The Rising Tide of Coronary Crisis: Decoding Age-Specific Disparities in Ischemic Heart Disease Burden Through the Global Burden of Disease Study 2021 Revelations: An Ecological Study.Health science reports · 2025Article
- Beyond Traditional Risk Calculators: The Expanding Role of Coronary Artery Calcium Scoring in Preventive Cardiology.Cureus · 2025Review
- Advancements in research to mitigate residual risk of atherosclerotic cardiovascular disease.European journal of medical research · 2025Review
- Applications of large language models in cardiovascular disease: a systematic review.European heart journal. Digital health · 2025Review
- Artificial intelligence to improve cardiovascular population health.European heart journal · 2025Review
- Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database.Journal of medical Internet research · 2025Article
- Machine Learning-Based Immuno-Inflammatory Index Integrating Clinical Characteristics for Predicting Coronary Artery Plaque Rupture.Immunity, inflammation and disease · 2025Article
- Article
- Cardiologists' knowledge and implementation of lifestyle counselling for cardiovascular disease prevention: A national survey.Bioinformation · 2024Article
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.
Funding
Abstract
purpose of reviewThis review evaluates how Artificial Intelligence (AI) enhances atherosclerotic cardiovascular disease (ASCVD) risk assessment, allows for opportunistic screening, and improves adherence to guidelines through the analysis of unstructured clinical data and patient-generated data. Additionally, it discusses strategies for integrating AI into clinical practice in preventive cardiology. RECENT
findingsAI models have shown superior performance in personalized ASCVD risk evaluations compared to traditional risk scores. These models now support automated detection of ASCVD risk markers, including coronary artery calcium (CAC), across various imaging modalities such as dedicated ECG-gated CT scans, chest X-rays, mammograms, coronary angiography, and non-gated chest CT scans. Moreover, large language model (LLM) pipelines are effective in identifying and addressing gaps and disparities in ASCVD preventive care, and can also enhance patient education. AI applications are proving invaluable in preventing and managing ASCVD and are primed for clinical use, provided they are implemented within well-regulated, iterative clinical pathways.
Indexed as
Identifiers
What Socratic 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 Socratic graph.