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Here are
82 public repositories
matching this topic...
A systems-level analysis engine that models sleep as a recovery debt process rather than a nightly outcome. Using physiological traits and ecological pressure signals, it estimates predicted sleep need, quantifies sleep debt, and visualizes how stress accumulates silently before visible fatigue or failure occurs.
👁 pinkrain_health_journal
Privacy-first personal health journal with experimental AI features. Track medications, journal symptoms, and explore on-device ML (for educational purposes)
The W4H Integrated Toolkit Repository provides a unified platform for managing, analyzing, and visualizing wearable health data using a suite of open-source tools and frameworks.
👁 dadpy
The swiss army knife for discharge abstract database (DAD).
Patient Reported Information Multidimensional Exploration (PRIME) is an automated platform to investigate Online Support Group (a.k.a. health forums, online health groups) discussions for investigation of individualised patient behaviours and patient information, over time.
MortalityMinder: an R-based, multi-view interactive presentation examining county-level factors associated with midlife mortality trends.
Milestone 2 project - Electronic Health Record Analysis and ICD Code Prediction
AI-powered health platform with multi-LLM engine (GPT-4o, Claude, Gemini). Workout generation, medication tracking with OCR, vision AI, gamification with leaderboards/rewards. Self-hosted, privacy-first.
Visualized 2015 U.S. health survey data to uncover risk factors and patterns associated with diabetes.
ClinicCare é um sistema de gestão para clínicas e consultórios, com agendamento, prontuários eletrônicos, controle financeiro e relatórios interativos. Desenvolvido com Dash e Plotly, possui interface responsiva, validações avançadas e foco em eficiência e segurança.
Mayo Clinic-grade Apple Health data analysis — Claude Code skill with 20 peer-reviewed statistical methods and 35+ SVG visualizations
Data analysis focusing on health problems
Data science project for diabetes risk analysis and classification using CDC BRFSS health indicators.
Developed a machine learning model for diabetes prediction, using patient data to provide early risk assessments and improve healthcare outcomes.
This project analyses the 2015 BRFSS health survey to identify key predictors of diabetes risk using data cleaning, statistical analysis, and machine‑learning models. BRFSS stands for Behavioral Risk Factor Surveillance System — a large, annual telephone‑based health survey run by the U.S. Centers for Disease Control and Prevention (CDC).
Comprehensive collection of 8 clinical data science and health analytics projects focusing on disease prediction, risk stratification, and treatment pattern analysis using advanced machine learning algorithms and statistical modeling. Portfolio: https://nana-safo-duker.github.io/
Explainable wellness intelligence platform for personalized protocols, biomarker trends, and wearable-driven daily guidance.
Machine learning project to predict obesity risk levels based on lifestyle and demographic data. This project utilizes advanced algorithms like CatBoost, LightGBM, and more to classify individuals into different obesity categories
An interactive web dashboard that analyzes Fitbit wearable data to provide personalized health insights, including activity trends, sleep correlations, and AI-powered calorie burn predictions.
👁 epidash
Interactive epidemiological dashboard visualizing disease trends across Kenya. Built with PHP, Chart.js, and Leaflet for the CEMA Software Engineering Internship.
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