ArticleJACC. Basic to translational science2021
Artificial Intelligence Models Reveal Sex-Specific Gene Expression in Aortic Valve Calcification.
Article in JACC. Basic to translational science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence technology in aortic valve disease: a decade of scientometric and narrative review.Frontiers in cardiovascular medicine · 2026Pooled it
- Global research trends and hotspots of artificial intelligence research in spinal cord neural injury and restoration-a bibliometrics and visualization analysis.Frontiers in neurology · 2024Pooled it
- A Review of Sex Differences in Patients with Aortic Stenosis: A Focus on Diagnostic and Treatment Differences, a Narrative Review.Journal of clinical medicine · 2026Review
- Spatial and Single-Cell Mapping Reveals Valvular Interstitial Cell and Macrophage Sex Differences in Calcific Aortic Valve Disease.Arteriosclerosis, thrombosis, and vascular biology · 2026Article
- Sex-Specific Prognostic Value of Aortic Valve Calcium and the Risk for Aortic Stenosis: Multi-Ethnic Study of Atherosclerosis (MESA).Circulation. Cardiovascular imaging · 2026Article
- A Transcriptomic Approach to Sex Differences in Calcific Aortic Valve Stenosis in Patients with a Tricuspid Aortic Valve.CJC open · 2025Article
- Calcific aortic stenosis: omics-based target discovery and therapy development.European heart journal · 2025Review
- Review
- Sex Differences in Aortic Stenosis: From the Pathophysiology to the Intervention, Current Challenges, and Future Perspectives.Journal of clinical medicine · 2024Review
- Valvular Endothelium: A Genetically Susceptible Predilection Site for Calcific Aortic Valve Stenosis.JACC. Basic to translational science · 2023Article
- Correlation between artificial intelligence-enabled electrocardiogram and echocardiographic features in aortic stenosis.European heart journal. Digital health · 2023Article
- Antiphospholipid antibodies in patients with calcific aortic valve stenosis.Rheumatology (Oxford, England) · 2023Article
- Cellular-scale sex differences in extracellular matrix remodeling by valvular interstitial cells.Heart and vessels · 2023Article
- The tyrosine kinase inhibitor nilotinib targets the discoidin domain receptor DDR2 in calcific aortic valve stenosis.British journal of pharmacology · 2022Article
- Sex differences in aortic stenosis: Identification of knowledge gaps for sex-specific personalized medicine.American heart journal plus : cardiology research and practice · 2022Article
- Incidence, associated outcomes, and predictors of upper gastrointestinal bleeding following acute myocardial infarction: a SWEDEHEART-based nationwide cohort study.European heart journal. Cardiovascular pharmacotherapy · 2022Article
- Calcific aortic valve stenosis and COVID-19: clinical management, valvular damage, and pathophysiological mechanisms.Cardiology plus · 2022Review
- Calcific aortic valve disease: from molecular and cellular mechanisms to medical therapy.European heart journal · 2022Article
- Investigating Genetic and Other Determinants of First-Onset Myocardial Infarction in Malaysia: Protocol for the Malaysian Acute Vascular Events Risk Study.JMIR research protocols · 2022Article
- Early Identification of Maternal Cardiovascular Risk Through Sourcing and Preparing Electronic Health Record Data: Machine Learning Study.JMIR medical informatics · 2022Article
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Male and female aortic stenosis patients have distinct valvular phenotypes, increasing the complexities in the evaluation of valvular pathophysiology. In this study, we present cutting-edge artificial intelligence analyses of transcriptome-wide array data from stenotic aortic valves to highlight differences in gene expression patterns between the sexes, using both sex-differentiated transcripts and unbiased gene selections. This approach enabled the development of efficient models with high predictive ability and determining the most significant sex-dependent contributors to calcification. In addition, analyses of function-related gene groups revealed enriched fibrotic pathways among female patients. Ultimately, we demonstrate that artificial intelligence models can be used to accurately predict aortic valve calcification by carefully analyzing sex-specific gene transcripts.
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