🍎 Pipeline for Processing SISVAN Microdata on Nutritional Status Monitoring in Brazil

Predict child malnutrition risk in Chad with machine learning to help health workers act early and target care

Analysis of 3 measurements of malnutrition in young children globally and comparing it to the COVID-19 death rates.

ML pipeline predicting child malnutrition risk in Chad using DHS 2014 survey data. Gradient Boosting achieved 92% accuracy and 0.979 AUC on 9,826 children. 52.9% of Chadian children under five are malnourished.

Dashboard for the app monitoring Community-based Management of Acute Malnutrition in Burundi

cause nutrition is a bitch

Malnutrition causing thousands of hospital admissions - get the data

ENSAE-ENSAI Formation Continue (Cepe)/OpenClassrooms Data Analyst 2022-2023 - Projet 4

This project uses facial landmark detection to analyze the nasal depth of children, aiming to contribute to malnutrition detection

An open-source Digital Tool for predicting acute childhood malnutrition risk in Kenya using machine learning and WHO Data Quality Review standards. This system provides county and sub-county level predictions of acute childhood malnutrition cases one month ahead, incorporating rigorous data quality monitoring and automated governance features.

AI-powered pediatric malnutrition detection and clinical screening SaaS platform using FastAPI, Next.js, Docker, OpenCV, WHO anthropometric scoring, and Grad-CAM explainability.