🍎 Pipeline for Processing SISVAN Microdata on Nutritional Status Monitoring in Brazil
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Updated
Dec 15, 2025 - R
🍎 Pipeline for Processing SISVAN Microdata on Nutritional Status Monitoring in Brazil
The Anthro Survey Analyser is a tool that allows the user to perform comprehensive analysis of anthropometric data for children under 5 years of age based on the WHO Growth Standards
Model performance with accuracy of 99.904%, precision of 99.871%, recall of 99.877%, and f1-score of 99.874% with 96799 training data and 24200 testing data.
predictive analysis yang dapat memprediksi tingkat risiko stunting pada anak berdasarkan faktor-faktor gizi dalam makanan ibu hamil, dengan tingkat akurasi yang tinggi.
This project will make predictions and a little PHP-based visualization, machine learning here will describe the predictions of whether you are stunting (nutritional problems) or not.
Analysis of 3 measurements of malnutrition in young children globally and comparing it to the COVID-19 death rates.
An AI-powered medical app addressing child stunting👶 innovatively optimizes growth and development, streamlining health monitoring, offering timely nutrition guidance, and transforming child care practices, potentially preventing long-term health issues for future generations 🥑.
👶ASING! Machine Learning Model (Bangkit Capstone Project 2024 Batch 1)
营养学 | 儿童青少年生长迟缓食养助手 (Childhood Stunting Dietary Guide) — 基于国家卫健委《儿童青少年生长迟缓食养指南(2023年版)》AI科普对话Skill · 使用WorkBuddy构建
Sistem Precision Targeting MBG berbasis Geospatial Machine Learning untuk mewujudkan SDG 2 Zero Hunger dan SDG 3 Good Health and Well-Being Indonesia
The factors influencing stunting in East Java in 2022 are analyzed using Geographically Weighted Regression (GWR) using R Studio
Aplikasi mobile BundaCare untuk memantau asupan nutrisi ibu hamil dengan deteksi makanan.
DICASTING (Digitalisasi Pencegahan Stunting) Kota Sawahlunto
MARS Modeling: Nutrition for Stunting in Depok, Indonesia
🗺️ Platform intelijen geospasial stunting Indonesia — 514 kab/kota, SSGI/Riskesdas/BPS, XGBoost+SHAP, MapLibre GL, LLM narratives
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