Python package for managing OHDSI clinical data models. Includes support for LLM based plain text queries, MCP server and FHIR import.
Secure, local, offline database for Garmin Connect health data. Windows desktop app, no setup needed. Built for long-term local analysis, dashboards, local AI and MCP-Server. Export your data as JSON, CSV and InfluxDB Line Protocol.
Track and visualize your blood test results over time with AI-powered data extraction
Python-based machine learning and data science module from SFSU developed for the NIGMS Sandbox project
An MCP server built on top of Huawei Training Camp (HTC) APIs, enabling AI agents to access and analyze Huawei Health training data.
The NHANES Data 'API' is a Python tool that simplifies access to the National Health and Nutrition Examination Survey (NHANES) dataset. This project provides an easy-to-use API to retrieve NHANES data, helping researchers, data scientists, health professionals, and other stakeholders access these valuable datasets.
Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.
An application for creating, validating, reusing and extending sets of clinical codes.
An Open Source python library for exploring glucose data along with the response to meals and exercise.
MusicPsychologyToolbox
Objective, create an intuitive and user-friendly web-based application for visualizing and exploring NHANES data. This dashboard will enable users, including those with limited or no Python programming experience, to interact with NHANES data and generate informative visualizations to gain insights into various health-related aspects.
VetSalud Database- Complete PostgreSQL solution for veterinary clinic management. Features: patient tracking, appointment scheduling, medical records, inventory control, audit trails, and business intelligence views. Production-ready.
Live births in Scotland 2021 - Exercise on spatial vector data with R - RMarkdown file
Full-stack AI-powered health analytics platform combining Oura biometric data with custom tag-based pattern analysis, enabling detection of relationships (e.g., symptoms, lifestyle factors) that are not accessible in the native Oura app.
A comparative study applying a stochastic Pure Death Process, Cox Proportional Hazards model, and logistic regression to breast cancer survival data from 272 Netherlands patients. Includes simulations, survival analysis, model diagnostics, and evaluation of hazard rate prediction across methods.
Privacy-first Apple Health & Apple Watch data analyzer for Windows. Imports HealthKit ZIP/XML locally, builds personal baselines, and explains sleep, heart rate, HRV, activity, blood oxygen and wrist-temperature trends with cross-metric evidence. Tauri · Rust · React. | 知衡健康
Presentation about the "self-controlled case series (SCCS)" method.
State-Level Risk Factor Analysis of Mental Health Wellbeing
Analysis of Hospital Admission Data Using Excel
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