🍎 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
predictive analysis yang dapat memprediksi tingkat risiko stunting pada anak berdasarkan faktor-faktor gizi dalam makanan ibu hamil, dengan tingkat akurasi yang tinggi.
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.
An end-to-end AI system for early stunting risk prediction using a synthetic dataset, explainable machine learning, FastAPI, and a modern web application.
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 🥑.
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.
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
👶ASING! Machine Learning Model (Bangkit Capstone Project 2024 Batch 1)
Analisis stunting data rutin SigiziKesga, Puskesmas Mumbulsari 2024–2026 (hasil agregat, tanpa data per anak)
Sistem Precision Targeting MBG berbasis Geospatial Machine Learning untuk mewujudkan SDG 2 Zero Hunger dan SDG 3 Good Health and Well-Being Indonesia
Aplikasi mobile BundaCare untuk memantau asupan nutrisi ibu hamil dengan deteksi makanan.
An interpretable machine learning study of child stunting in Indonesia, covering provincial clustering, four-class classification, HAZ/WAZ regression, and an interactive dashboard.
The factors influencing stunting in East Java in 2022 are analyzed using Geographically Weighted Regression (GWR) using R Studio
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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