OpenHealthForAll: AI assistant for personal health data management, uploading examination reports to customize health plans

General Introduction

OpenHealthForAll is an open source project designed to help users manage and understand their personal health data. By leveraging artificial intelligence technology, OpenHealthForAll provides a locally run health assistant to help users better manage and analyze their health information. The program supports a variety of data sources, including blood test results, health screening data, personal body information and family medical history. Users can centralize this data on a single platform for intelligent parsing and structuring to enable personalized health management.

Function List

• Centralized health data entry: Easily centralize all your health data on one platform.
• intelligent parsing (math.): Automatically parses health data and generates structured data files.
• contextual dialog: Use structured data to personalize interactions with GPT-driven AI.
• Supports multiple data sources: Includes blood test results, health screening data, personal physical information and family medical history.
• Support for multilingual models: e.g. LLaMA, DeepSeek-V3, GPT, Claude, Gemini, etc.

Using Help

Installation process

1. clone warehouse: Run in a terminal git clone https://github.com/OpenHealthForAll/open-health.git Cloning Project Warehouse.
2. Installation of dependencies: Go to the project directory and run npm install Install the required dependencies.
3. Configuration environment: Reproduction .env.example file and rename it .env, modify the configuration as needed.
4. Initiation of projects: Run npm run dev Start the local development server.

Guidelines for use

1. data entry: Enter or upload health data on the platform, including blood test results, health check data, etc.
2. data parsing: The system automatically parses the input data and generates structured data files.
3. Personalized Interaction: Use the parsed data to talk to an AI assistant for personalized health advice.
4. data management: Users can view, edit and manage entered health data at any time.

Detailed Operation Procedure

• Centralized health data entry: In the "Data Entry" module of the platform, users can select different types of data (e.g. blood test results, health check data, etc.) for input or upload. The system will automatically recognize and parse these data.
• intelligent parsing (math.)Data input: After data input, the system will automatically parse and generate structured data files, and users can view the parsing results in the "Data Management" module.
• contextual dialogIn the "AI Assistant" module, users can use the parsed data to talk to the AI assistant, who will provide personalized advice and guidance based on the user's health data.
• Supports multiple data sourcesThe platform supports the input of multiple data sources, including blood test results, health check data, personal body information and family medical history. Users can add and manage different data sources in the "Data Source Management" module.
• Support for multilingual models: The platform integrates multiple language models, such as LLaMA, DeepSeek-V3, GPT, Claude, Gemini, etc., so that users can choose different models to interact with according to their needs.