ReviewNPJ cardiovascular health2024
Artificial intelligence bias in the prediction and detection of cardiovascular disease.
Review in NPJ cardiovascular health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Beyond Traditional Risk Scores: Artificial Intelligence in Coronary Plaque Characterization and Personalized Atherosclerosis Management.Journal of cardiovascular development and disease · 2026Review
- Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- Integrating Conventional and Emerging Approaches in Cardiovascular Risk Assessment and Management.Public health challenges · 2026Review
- Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Large language models approach clinician performance in ESC cardiovascular risk stratification: a vignette-based benchmark study.European heart journal. Digital health · 2026Article
- Advancing neurotech justice in youth digital mental health: insights from an interdisciplinary and cross-generational workshop.NPP - digital psychiatry and neuroscience · 2026Review
- The digital divide in cardiovascular care: who gets left behind?European heart journal. Digital health · 2026Article
- AI-driven cardiovascular risk prediction in patients with diabetes: bridging algorithmic innovation to equitable clinical application.Frontiers in medicine · 2026Article
- Rethinking Secondary Cardiovascular Prevention in the Digital Era: Patient Empowerment, Adherence and Optimisation of Guideline-based Care.European cardiology · 2026Review
- Artificial intelligence-enabled electrocardiography from scientific research to clinical application.EMBO molecular medicine · 2026Review
- The expanding role of artificial intelligence in personalised medicine: from innovation to individualized care.Frontiers in medicine · 2026Review
- Precision medicine and personalized nursing in cardiovascular disease: clinical applications and frontier developments.Frontiers in cardiovascular medicine · 2026Review
- Artificial Intelligence-Driven Wearable and Connected Technology for Allergy: Real-Time Monitoring and Predictive Management for Personalized Care.The journal of allergy and clinical immunology. In practice · 2025Review
- Review
- Great debate: artificial intelligence will replace much of what cardiologists do.European heart journal · 2025Article
- Review
- Advancements in Sensor Technology for Monitoring and Management of Chronic Coronary Syndrome.Sensors (Basel, Switzerland) · 2025Review
- Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025Review
- Promises and perils of generative artificial intelligence: a narrative review informing its ethical and practical applications in clinical exercise physiology.BMC sports science, medicine & rehabilitation · 2025Review
- Non-invasive Assessment of Coronary Artery Disease: The Role of AI in the Current Status and Future Directions.Cureus · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AI algorithms can identify those at risk of cardiovascular disease (CVD), allowing for early intervention to change the trajectory of disease. However, AI bias can arise from any step in the development, validation, and evaluation of algorithms. Biased algorithms can perform poorly in historically marginalized groups, amplifying healthcare inequities on the basis of age, sex or gender, race or ethnicity, and socioeconomic status. In this perspective, we discuss the sources and consequences of AI bias in CVD prediction or detection. We present an AI health equity framework and review bias mitigation strategies that can be adopted during the AI lifecycle.
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.