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PathoScan 🧪

Streamlit App OpenRouter Powered Demo


PathoScan Logo

🌱 Why I Built This

Last June, I got my blood test done. Like many people, I received a dense report full of medical jargon and numbers that didn’t mean much to me. I wanted to understand the abnormalities, see what values were connected, and learn what it meant for my body — but in simple language.

That experience led me to create PathoScan — a tool to help anyone turn medical pathological data into simple to understand report.


🧠 What is PathoScan?

PathoScan is an intelligent blood test analyzer powered by AI. Upload your blood test report, and let it:

  • 🧪 Analyze abnormal values in your test
  • 🩺 Identify potential health issues
  • 🌿 Recommend lifestyle changes based on the data

It’s built using Streamlit, LangChain, and OpenRouter models working together in an agentic workflow.


📽️ Demo

PathoScan_V2


🤖 Behind the Scenes

PathoScan uses a modular, agent-based architecture with 3 core tools:

Tool Purpose
BloodTestAnalyzer Extracts and explains abnormal values
HealthIssueIdentifier Maps findings to possible health conditions
LifestyleAdvisor Recommends simple lifestyle improvements

The agent evaluates your input and calls each tool only when relevant. All outputs are structured, readable, and optionally extracted as JSON for further use.


💬 AI Chatbot Assistant

Once your report is analyzed, you can chat directly with an AI assistant that knows your blood test insights.

How it works:

  • The chatbot is context-aware — it has access to your test insights (blood abnormalities, issues, recommendations).
  • Ask follow-up questions like:
    • “What does high LDL mean for me?”
    • “What should I eat to improve liver health?”
    • “Are these thyroid results serious?”

It's a powerful way to get tailored answers in natural language — all within your browser.


🚀 How to Run Locally

1. Clone the repo

git clone https://github.com/akarshghildyal/pathoscan_v2.git
cd pathoscan_v2

2. Install dependencies

pip install -r requirements.txt

3. Add your OpenRouter API key

Create a .env file in the project root with the following content:

OPENROUTER_API_KEY=your_openrouter_key

4. Launch the app

streamlit run app.py

✅ Features

  • Supports standard PDF blood test reports

  • Clean, simple Streamlit UI

  • Easy-to-understand explanations

  • Privacy-first: No data is stored or sent anywhere

  • Built-in chatbot for contextual queries


Made with ❤️ to bring clarity to your health.

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