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Running
Running
| * [ ] Gather ICD-10 data | |
| * [x] Obtain dataset from CMS/CDC or Kaggle | |
| * [ ] Download CSV of ICD-10-CM codes (\~70k entries) | |
| * [ ] Load data into application or database | |
| * [ ] Build search/lookup functionality | |
| * [ ] Implement keyword filter for description matching | |
| * [ ] Generate embeddings for each ICD description (offline) | |
| * [ ] Build vector index (FAISS, Annoy, or numpy) | |
| * [ ] Embed user query and perform nearest-neighbor search | |
| * [ ] Combine code and description lookup into MCP API | |
| * [ ] Accept input as code (lookup definition) or description (search codes) | |
| * [ ] Return list of candidate codes with descriptions | |
| * [ ] Integrate LLM for refinement (optional) | |
| * [ ] Use GPT-4 or Claude to select best code from top-N results | |
| * [ ] Prompt LLM to generate short rationale for selected code | |
| * [ ] Cache LLM prompts and responses to conserve tokens | |
| * [ ] Build MCP server (Gradio App) | |
| * [ ] Create Gradio UI with text input and output area | |
| * [ ] Implement backend logic to expose API endpoint or STDIO interface per MCP standards | |
| * [ ] Tag Space with “mcp-server-track” and configure /api route | |
| * [ ] Test connectivity with MCP client (e.g., Cursor IDE or Claude Desktop) | |
| * [ ] Test with realistic inputs | |
| * [ ] Simple case: “Type 1 diabetes mellitus” → expect E10.9 | |
| * [ ] Complex case: “Acute MI involving LAD” → expect I21.02 or related code | |
| * [ ] Edge case: Typos or layman terms (e.g., “heart attack”) → verify semantic search or add spell-check | |
| * [ ] Compare tool output to expected codes (use ChatGPT or reference lists) | |
| * [ ] Optimize and cache | |
| * [ ] Precompute embeddings for entire code database | |
| * [ ] Cache embeddings of frequent queries | |
| * [ ] Cache LLM explanations in memory or simple key-value store | |
| * [ ] Choose deployment hardware (GPU-backed if running local embedding model; CPU if precomputed) | |
| * [ ] Polish documentation & demo | |
| * [ ] Write README.md with tool description, architecture outline, research citations, and sponsor acknowledgments | |
| * [ ] Prepare 2–3 minute demo video showing Gradio UI and AI agent calling the MCP server | |
| * [ ] Share project on community channels (Discord, YouTube) for feedback and visibility | |