ReviewNPJ cardiovascular health2025
Leveraging AI-enhanced digital health with consumer devices for scalable cardiovascular screening, prediction, and monitoring.
Review in NPJ cardiovascular health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 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
28 citing papers in PubMed.
- Nurses' Engagement in Digital Health Clinical Trials Using Unobtrusive Monitoring Technologies: Constructivist Grounded Theory Study.Journal of medical Internet research · 2026Article
- Wearable Devices in Cardiovascular Care: A Narrative Review of the Transition Toward Predictive, Preventive, Personalized, and Participatory Medicine.Healthcare (Basel, Switzerland) · 2026Review
- Precision medicine in low-income settings and small island developing states.Nature reviews. Endocrinology · 2026Review
- De-risking Atrial Fibrillation: Refining Anticoagulation Decision-Making.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- [Atrial fibrillation in primary care: Towards a proactive risk-based model focused on early prevention].Atencion primaria · 2026Article
- Artificial intelligence and the evolution of the electrocardiogram: from cardiovascular diagnostic tool to digital biomarker.European heart journal. Digital health · 2026Review
- Sustained Reduction in Cardiopulmonary Fitness in Long COVID: A Report from the RECOVER-adult Cohort Study.JACC. Advances · 2026Article
- Wearable Devices and Data Sharing in the US.JAMA network open · 2026Article
- Nanostructured electrode materials and flexible-substrate engineering for wearable multi-analyte biosensors in diabetes monitoring and personalized care: a comprehensive review.Journal of materials science. Materials in medicine · 2026Review
- The Evolving Utility of Artificial Intelligence-Based Tools for the Detection of Heart Failure and Cardiomyopathies: From Potential to Implementation.Current heart failure reports · 2026Review
- From Biosignals to Bedside: A Review of Real-Time Edge Machine Learning for Wearable Health Monitoring.Bioengineering (Basel, Switzerland) · 2026Review
- Wearable-Echo-FM: an ECG echo foundation model for 1-lead electrocardiography.European heart journal. Digital health · 2026Article
- Sex-Specific Health and Economic Benefits in Older Women at Risk of Atrial Fibrillation: A Proof-of-Concept Evaluation of an AI-Enabled Strategy for Early Thromboembolic Risk Detection.Journal of clinical medicine · 2026Article
- Multi-sensor wearables for chronic heart failure: From signal-rich devices to equitable, implementable pathways.The Indian journal of medical research · 2026Article
- AI-Enabled Sensor Technologies for Remote Arrhythmic Monitoring in High-Risk Cardiomyopathy Genotypes.Sensors (Basel, Switzerland) · 2026Review
- Silent Myocardial Infarction Revisited: Immuno-metabolic Mechanisms, Multimodal Biomarkers, and Translational Diagnostics.Journal of cardiovascular translational research · 2026Review
- Distributed Precision Stroke Care: Artificial Intelligence-Driven Stroke Management Using Multimodal Sensor Data.Stroke · 2026Review
- Cardiovascular risk stratification without recalibration: A comparative study of the PREVENT and WHO risk scores in a multiethnic Brazilian cohort.American journal of preventive cardiology · 2026Article
- Reliability of Handheld Ultrasound Assessment of Brachial Artery Flow-Mediated Dilation Using AI-Assisted Automated Analysis in Postmenopausal Women.Medicina (Kaunas, Lithuania) · 2026Article
- Medical AI across Data Regimes to Promote Proactive Health.Health data science · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Traditional cardiovascular care relies on episodic, resource-intensive evaluations. Consumer wearable and portable devices, combined with artificial intelligence (AI), offer a scalable, low-cost alternative. These devices can enhance care with high-fidelity cardiovascular data captured outside traditional care settings, with AI further increasing their value. This review explores how AI-enhanced digital health tools can transform cardiovascular care, improving early detection, personalized risk assessment, and proactive management, particularly in resource-constrained settings, while bridging gaps in traditional care models.
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.