ReviewNature reviews. Cardiology2021
Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management.
Review in Nature reviews. Cardiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06993415 (Optimize Risk Prediction After Myocardial Infarction Through Artificial Intelligence and Multidimensional Evaluation), which is not on this map. Cited by 96 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.
Optimize Risk Prediction After Myocardial Infarction Through Artificial Intelligence and Multidimensional Evaluation: The ORACLE Study
Who cites it
96 citing papers in PubMed, 2 syntheses or guidelines pooled it, 221 citations in OpenAlex.
- Artificial Intelligence Applications in Medical Devices for Personalized Health Care Solutions: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Device-based remote monitoring strategies for congestion-guided management of patients with heart failure: a systematic review and meta-analysis.European journal of heart failure · 2022Pooled it
- Home-Based Cardiac Rehabilitation Using a Smart Ring and Telephone Counselling: A Randomized Controlled Trial.Journal of Korean medical science · 2026Trial
- Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease.Scientific reports · 2023Trial
- AI Cautionary Guide: Pitfalls and Strategies for the Use of Machine Learning in Medical Research.Clinical pharmacology and therapeutics · 2026Review
- Operationalizing AI-Enabled Cardiovascular Biomarkers: A Clinician-Centered Framework for Validation, Governance, and Workflow Integration.JMIR cardio · 2026Article
- Mechanical Contact Conditions in Wearable Reflectance Photoplethysmography: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Automated cardiac arrest detection using wrist-derived photoplethysmography during withdrawal of life-sustaining treatment: a prospective clinical validation study.The Lancet regional health. Europe · 2026Article
- Echocardiographic Phenomapping in HFpEF: From Imaging Biomarkers to Precision Cardiovascular Medicine.Echocardiography (Mount Kisco, N.Y.) · 2026Review
- Contemporary Management of Aortic Stenosis: Timing of Intervention and Lifetime Valve Management.European journal of clinical investigation · 2026Review
- Self-powered in-stent restenosis diagnosis via magnetoelastic stents.Nature cardiovascular research · 2026Article
- Anesthesia for cesarean delivery in the era of artificial intelligence: a narrative review.Journal of anesthesia, analgesia and critical care · 2026Review
- Machine learning in cardiology education: preparing the next generation for the AI era.The British journal of cardiology · 2026Article
- Access to digital health technologies: personalized framework and global perspectives.Nature reviews. Cardiology · 2026Review
- Minimally Invasive and in Situ Capacitive Sensing of Cardiac Troponin I from Interstitial Fluid.ACS sensors · 2025Article
- Characterizing industry payments for FDA-approved AI medical devices.Health affairs scholar · 2025Article
- A textile-based alignment-free electrophysiological sensing sleeve for comprehensive cardiovascular monitoring.Microsystems & nanoengineering · 2025Article
- Artificial intelligence-derived photoplethysmography age as a digital biomarker for cardiovascular health.Communications medicine · 2025Article
- Thinned and Welded Silver Nanowires for Intelligent Pressure and Humidity Sensing Enabled by Machine Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Integrating Large-Scale Data Analytics for Cardiovascular Disease Prediction: A Scoping Review.Healthcare informatics research · 2025Article
36 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 6 institutions in 1 country.
Funding
Abstract
Ambulatory monitoring is increasingly important for cardiovascular care but is often limited by the unpredictability of cardiovascular events, the intermittent nature of ambulatory monitors and the variable clinical significance of recorded data in patients. Technological advances in computing have led to the introduction of novel physiological biosignals that can increase the frequency at which abnormalities in cardiovascular parameters can be detected, making expert-level, automated diagnosis a reality. However, use of these biosignals for diagnosis also raises numerous concerns related to accuracy and actionability within clinical guidelines, in addition to medico-legal and ethical issues. Analytical methods such as machine learning can potentially increase the accuracy and improve the actionability of device-based diagnoses. Coupled with interoperability of data to widen access to all stakeholders, seamless connectivity (an internet of things) and maintenance of anonymity, this approach could ultimately facilitate near-real-time diagnosis and therapy. These tools are increasingly recognized by regulatory agencies and professional medical societies, but several technical and ethical issues remain. In this Review, we describe the current state of cardiovascular monitoring along the continuum from biosignal acquisition to the identification of novel biosensors and the development of analytical techniques and ultimately to regulatory and ethical issues. Furthermore, we outline new paradigms for cardiovascular monitoring.
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.