🍎 Pipeline for Processing SISVAN Microdata on Nutritional Status Monitoring in Brazil
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
Predict child malnutrition risk in Chad with machine learning to help health workers act early and target care
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
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