Precision biomarker discovery in hypertension through explainable AI and proteomics
AI identifies eight blood proteins that signal early high blood pressure, revealing oxidative stress and vessel function pathways.
Explainable AI applied to plasma proteomics of 778 Qatar Biobank participants identified 8 candidate circulating biomarkers for stage-1 hypertension with AUROC 0.80, implicating oxidative stress and vascular function pathways. While validation in diverse cohorts is needed, this study demonstrates a replicable framework for AI-driven cardiovascular biomarker discovery.
What the study was
- Study design
- Cross-sectional ML biomarker discovery study
- Population
- Qatar Biobank participants: 554 controls, 224 stage-1 hypertension cases
- Sample size
- 778
- Category
- Diagnostics
- Maturity
- Exploratory
- Journal
- Journal of Human Hypertension
Why it surfaced
n=778; AUROC 0.80 with SHAP interpretability; explainable AI + proteomics framework is reproducible and relevant to AI/ML diagnostics watchlist.
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