Clinical Copilot Dashboard

A Streamlit-based dashboard for clinicians to monitor patient vitals, trends, and alerts.

Features

• Patient overview with key vitals and alerts
• Interactive trend visualizations for cardiometabolic data, weight/BMI, and mood
• Active problems and recent lab results
• Color-coded KPIs for quick assessment
• Responsive design for different screen sizes

Getting Started

Prerequisites

• Python 3.8+
• pip (Python package manager)

Installation

1. Clone the repository:

   git clone <repository-url>
   cd mcp-hackathon-project

2. Navigate to the dashboard directory:

   cd dashboard

3. Install the required packages:

   pip install -r requirements.txt

Running the Dashboard

1. Start the Streamlit application:

   streamlit run clinical_copilot.py

2. The dashboard will open automatically in your default web browser. If it doesn't, navigate to:

   http://localhost:8501
   

Usage

• Use the sidebar to select different patients
• View color-coded KPIs for quick assessment
• Navigate between different trend tabs to see historical data
• Check the alerts section for important notifications
• View active problems and recent lab results

File Structure

dashboard/
├── clinical_copilot.py     # Main Streamlit application
├── requirements.txt         # Python dependencies
└── data/                    # Patient data directory
    └── patient_1.json       # Example patient data (if available)

License

This project is licensed under the MIT License - see the LICENSE file for details.