patient-data

SmartChart & the Deployable Medical Assistance Case

Validate FHIR resources directly in your browser. This open-source tool checks required fields, highlights missing elements, and flags invalid values for common resource types—all without server dependencies. Ideal for quick diagnostics, learning FHIR structure, or validating profiles securely.

Interactive Streamlit dashboard: 1,000 patient records, 10 diseases, 8 visualization sections, correlation heatmaps, real-time KPIs

Medical records scattered across Gmail and Google Drive? Oncofiles reads, organizes, and makes them available through AI. For cancer patients and caregivers. Works with Claude & ChatGPT.

小胰宝社区出品的个人病情管理智能体客户端

COVID-19 Power BI Dashboard analyzing patient outcomes across administrative, clinical, comorbidities, and demographic factors

In this project, I used a dataset with over 1000 rows of information about various patients and analyzed the data in SQL.

A simple, browser-based patient registration prototype that demonstrates how patients can securely submit their basic details through a digital form. Built as a concept to explore digital health workflows. This is not a production-ready system and should not be used for handling real patient data.

Driving Data Informed Healthcare Decisions

HealthTrackPro is a React Native mobile app for healthcare providers to track and monitor patient data. It allows adding and viewing patient records, managing clinical data like blood pressure and heart rate, and alerting providers to critical conditions. Designed for efficient healthcare data management with an intuitive interface.

Secure, HIPAA-compliant infrastructure blueprint for patient data interoperability and AI-driven diagnostic insights.

An android application for doctors, chemists and other medical staff to store their patients data in a very convenient way - JUST LIKE WE USE WHATSAPP

GPOC – a free, open-source, patient co-owned health record. Developed by GlobeDoc Research Hub.

Introduction to PERMIT project resources

In this project, different machine learning approaches are used to detect the diabetes in patients using the PIMA Indians diabetes dataset.

Analysis of patient data from a kaggle dataset to assess if tall people's risk of developing cardiovascular disease was higher than short people's.

It’s a reactive health monitoring system that simulates patients’ vital tracking with real-time sensor data, stream processing, and alert generation — a complete hands-on project to showcase RxJava expertise.

OpenPCM Server

A web app built for the general public - teachers, employers, doctors, etc. - to visualize an infection in a network of patients. Built with an algorithm prototype to find patient zero.