Orchestrates AI workflows for healthcare applications using a graph-based architecture.
Sponsored
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.
Características Principales
01Orchestrates multi-agent AI systems using graph-based architectures
02Demonstrates connecting multiple AI providers in healthcare workflows
03Supports text, image, and speech generation within a single system
04Implements medical prediction using Model Context Protocol (MCP)
05Utilizes Polars for serving CSV files in the MCP server
063 GitHub stars
Casos de Uso
01Nutrition assessment using multiple AI models
02Multi-modal AI system for text, image, and speech generation
