Identify Missing Information in Patient Medical Histories

An explainable medical agent that detects missing information in patient stories, asks the next most important question, and provides full traceability and reasoning for every decision.

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Inspiration

We wanted to solve the critical issue of incomplete medical histories, which often hide red flags and lead to delayed or incorrect diagnoses.

What it does

It detects missing information in patient stories, asks the next essential question, logs all reasoning, and produces a transparent clinical summary.

How we built it

We built a structured Glass-Box agent using Claude 3.5 Sonnet, strict JSON outputs, reasoning logs, error handling, and a full trace pipeline.

Built With

  • aws-bedrock
  • claude-3.5-sonnet
  • google-colab
  • holistic-ai-sdk
  • json
  • jupyter-notebook
  • langchain
  • python
  • structured
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