IntelliNode Medical
Orchestrates AI workflows for healthcare applications using a graph-based architecture.
About
IntelliNode Medical provides educational examples demonstrating how multi-agent systems, orchestrated via a graph-based architecture, can be applied to healthcare and wellness scenarios. The repository includes Jupyter Notebook labs that showcase nutrition assessment using OpenAI and Anthropic models, multi-modal AI systems integrating text, image, and speech generation, and medical prediction systems using Model Context Protocol (MCP) served with a Polars backend. Note that these examples are for educational purposes only and not intended for real patient care.
Key Features
- Orchestrates multi-agent AI systems using graph-based architectures
- Demonstrates connecting multiple AI providers in healthcare workflows
- Supports text, image, and speech generation within a single system
- Implements medical prediction using Model Context Protocol (MCP)
- Utilizes Polars for serving CSV files in the MCP server
- 3 GitHub stars
Use Cases
- Nutrition assessment using multiple AI models
- Multi-modal AI system for text, image, and speech generation
- Medical prediction from clinical data using MCP
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