Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Busayo-18/ai-telehealth-cvd-risk-prediction

Domaine:

healthcare

Type de record:

software
Créateur:
Bus
Hôte:
An AI-powered telehealth system fpr early hypertension and cardiovascular disease risk screening using machine learning . Designed to improve early detection and healthcare accessibility in Africa. # ai-telehealth-cvd-risk-prediction An AI-powered telehealth system for early hypertension and cardiovascular disease risk screening using machine learning . Designed to improve early detection and healthcare accessibility in Africa. # AI-Telehealth: CVD Risk Prediction (Group 9) ## 🩺 Project Overview This project focuses on predicting hypertension and cardiovascular risk within the African context. We developed a machine learning pipeline that analyzes patient demographics, lifestyle factors (stress, income, education), and medical vitals to provide early risk assessment. ## 🚀 Key Features - **Data Cleaning & Engineering:** Handled categorical encoding and introduced realistic lifestyle features (Stress Level, Sleep Patterns). - **Model Shootout:** Compared Random Forest, Logistic Regression, and SVM to find the most accurate predictor. - **Robustness:** Introduced 10% noise to simulate real-world diagnostic uncertainty, achieving a realistic **90.15% accuracy**. - **Deployment Ready:** Exported the winning model as a `.pkl` file for integration into telehealth platforms. ## 📊 Technical Results - **Final Model:** Random Forest (Winning Algorithm) - **Accuracy:** 90.15% - **Key Predictors:** Age, Stress Levels, and BMI. ## 🛠️ Installation ```bash pip install -r requirements.txt

Visit

github.com