Phawazz/HyperSense

XGBoost + SHAP hypertension risk screener trained on Ghana & Benin DHS data. Non-invasive. Explainable. Built for West Africa. ### Explainable AI-Powered Hypertension Risk Screening for West Africa *Answer a few questions. Know when to get checked.* **→ Try HyperSense Live** --- ## What Is HyperSense? HyperSense is an explainable machine learning system that estimates an individual's likelihood of hypertension using six non-invasive inputs — no clinical equipment, no blood test, no blood pressure cuff required. Given **age, sex, place of residence, education level, tobacco use, and BMI**, HyperSense returns: - A **hypertension risk tier** (High / Low) - A **probability estimate** of elevated blood pressure - A **SHAP-based explanation** of the personal factors driving the result - A **personalised recommendation** for preventive action > ⚠️ **HyperSense is a screening and awareness tool. It does not diagnose hypertension. All results should be confirmed with a measured blood pressure reading from a trained healthcare professional.** --- ## Why It Was Built Hypertension affects an estimated **38.1% of Nigerian adults (age-standardised)**, yet *only 60%* of those affected are aware of their condition, roughly *a third* receive treatment, and *just 12%* achieve blood pressure control (Odili et al., Glob Heart, 2020 — WHO STEPwise nationwide survey). Existing risk prediction tools — including the **Framingham Risk Score, ASCVD Pooled Cohort Equations, and ESH/ESC 2018 models** — were derived from predominantly Western cohorts. They may not accurately reflect the epidemiological, dietary, and demographic characteristics of West African populations. HyperSense was built to address two simultaneous gaps: 1. **The tool gap** — no publicly accessible, non-invasive hypertension screener calibrated for West African populations 2. **The data gap** — Nigeria's national health surveys collect no measured blood pressure data, a surveillance failure documented and reported as part of this project --- ## Data Sources HyperSense is trained on **fieldworker-measured blood pressure data …