ArticleGenes2020
A Machine Learning Model Utilizing a Novel SNP Shows Enhanced Prediction of Coronary Artery Disease Severity.
Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 27 citations in OpenAlex.
- A prevalent disease-associated SNP in the humanNAR molecular medicine · 2026Article
- Effect of Interactions Between Endothelial Lipase Gene Polymorphisms and Traditional Cardiovascular Risk Factors on Coronary Heart Disease Susceptibility.Reviews in cardiovascular medicine · 2025Article
- AI-powered precision medicine: utilizing genetic risk factor optimization to revolutionize healthcare.NAR genomics and bioinformatics · 2025Review
- Transforming Cardiovascular Risk Prediction: A Review of Machine Learning and Artificial Intelligence Innovations.Life (Basel, Switzerland) · 2025Review
- Clinical associations and potential cellular mechanisms linking G6PD deficiency and atherosclerotic cardiovascular disease.npj metabolic health and disease · 2025Review
- Efficacy of artificial intelligence-based FFR technology for coronary CTA stenosis detection in clinical management of coronary artery disease: a systematic review.Frontiers in physiology · 2025Review
- The landscape of very important pharmacogenes variants and potential clinical relevance in the Chinese Jingpo population: a comparative study with worldwide populations.Cancer chemotherapy and pharmacology · 2024Article
- An In-Depth Insight into Clinical, Cellular and Molecular Factors in COVID19-Associated Cardiovascular Ailments for Identifying Novel Disease Biomarkers, Drug Targets and Clinical Management Strategies.Archives of microbiology & immunology · 2024Article
- Machine Learning in Cardiovascular Risk Prediction and Precision Preventive Approaches.Current atherosclerosis reports · 2023Review
- Using Machine Learning Methods in Identifying Genes Associated with COVID-19 in Cardiomyocytes and Cardiac Vascular Endothelial Cells.Life (Basel, Switzerland) · 2023Article
- Prediction of medication-related osteonecrosis of the jaws using machine learning methods fromFrontiers in medicine · 2023Article
- Current and Future Applications of Artificial Intelligence in Coronary Artery Disease.Healthcare (Basel, Switzerland) · 2022Review
- Efficient Model for Coronary Artery Disease Diagnosis: A Comparative Study of Several Machine Learning Algorithms.Journal of healthcare engineering · 2022Article
- Machine learning for infection risk prediction in postoperative patients with non-mechanical ventilation and intravenous neurotargeted drugs.Frontiers in neurology · 2022Article
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 2 institutions in 1 country.
Funding
Abstract
PubMed holds no abstract for this paper.
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.