https://github.com/jerryblessed/patho-scope
https://github.com/jerryblessed/patho-scope
Last synced: 9 months ago
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- Host: GitHub
- URL: https://github.com/jerryblessed/patho-scope
- Owner: Jerryblessed
- Created: 2025-06-17T11:31:11.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-17T11:53:33.000Z (about 1 year ago)
- Last Synced: 2025-06-17T12:42:04.809Z (about 1 year ago)
- Language: Python
- Size: 26 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🧠Patho-Scope AI
An Intelligent Digital Workbench for Histopathology Analysis. Patho-Scope AI uses a locally trained TensorFlow model to classify histopathology images into five cancer types, then leverages Google Gemini for AI-generated medical explanations. It is built as a lightweight Flask web application with MongoDB storage.
---
## 📦 Installation Guide (Flask Version)
### 1. Clone the Repository
```bash
git clone https://github.com/Jerryblessed/Patho-Scope.git
cd Patho-Scope
```
### 2. Create a Virtual Environment
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
### 3. Install Python Dependencies
```bash
pip install -r requirements.txt
```
### 4. Set Up Environment Variables
Create a `.env` file in the root directory:
```env
MONGO_URI=your_mongodb_connection_string
GEMINI_API_KEY=your_google_gemini_api_key
```
### 5. Add the Trained Model
Ensure the model file `histo_densenet121_model.keras` is in the project root directory.
### 6. Run the Flask App
```bash
flask run
```
Visit the app at: [http://localhost:5000](http://localhost:5000)
---
You're now ready to use Patho-Scope AI for AI-assisted histopathology diagnosis.