ReviewHeart failure clinics2022
Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure.
Review in Heart failure clinics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.
- Chatbot Artificial Intelligence for Genetic Cancer Risk Assessment and Counseling: A Systematic Review and Meta-Analysis.JCO clinical cancer informatics · 2023Pooled it
- Racial and Ethnic Disparities in the Utilization and Outcomes of Catheter Ablation for Atrial Fibrillation and Flutter: a State-of-the-Art Review.Current cardiology reports · 2026Review
- Recommended guidelines concerning artificial intelligence and health equity: a scoping review.Health affairs scholar · 2026Review
- Knowledge Architecture for Race and Ethnic Group Defining in Learning Health Systems.Learning health systems · 2026Article
- Implementation of Machine Learning in Heart Failure Trials.Current heart failure reports · 2026Review
- Nurse-Led, Remote Optimisation of Guideline-Directed Medical Therapy in Patients with Heart Failure and Reduced Ejection Fraction Across Australia.Journal of clinical medicine · 2025Article
- Review
- Diversity and Inclusion Within Datasets in Heart Failure: A Systematic Review.JACC. Advances · 2025Article
- Can AI developers avoid bias in public health applications?Frontiers in public health · 2025Article
- Artificial Intelligence to Promote Racial and Ethnic Cardiovascular Health Equity.Current cardiovascular risk reports · 2024Article
- Article
- Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?Current atherosclerosis reports · 2024Review
- Health Equity: A Call to Action for Innovators, Clinical Leaders, and Policymakers.JACC. Advances · 2024Article
- Implementation Science to Achieve Equity in Heart Failure Care: A Scientific Statement From the American Heart Association.Circulation · 2024Review
- Review
- Catalyzing Restructure of a Broken Health Care System.Circulation. Cardiovascular quality and outcomes · 2024Article
- Telehealth and Health Equity in Older Adults With Heart Failure: A Scientific Statement From the American Heart Association.Circulation. Cardiovascular quality and outcomes · 2023Review
- Guiding principles for the responsible development of artificial intelligence tools for healthcare.Communications medicine · 2023Review
- Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.Journal of the American Heart Association · 2023Article
- Misguided Artificial Intelligence: How Racial Bias is Built Into Clinical Models.The Brown journal of hospital medicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 6 institutions in 1 country.
Funding
Abstract
Patients with heart failure (HF) are heterogeneous with various intrapersonal and interpersonal characteristics contributing to clinical outcomes. Bias, structural racism, and social determinants of health have been implicated in unequal treatment of patients with HF. Through several methodologies, artificial intelligence (AI) can provide models in HF prediction, prognostication, and provision of care, which may help prevent unequal outcomes. This review highlights AI as a strategy to address racial inequalities in HF; discusses key AI definitions within a health equity context; describes the current uses of AI in HF, strengths and harms in using AI; and offers recommendations for future directions.
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.