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delirium-scorecard

An application to predict delirium prevalence rates at hospitals.

This is a Next.js application that displays delirium prevalence rates at hospitals. It uses a React frontend with a clean, clinical dashboard interface.

Prerequisites

Before you begin, ensure you have the following installed:

  • Node.js (version 14 or later)
  • npm (usually comes with Node.js)

Getting Started

To get the application running on your local machine, follow these steps:

  1. Clone the repository:
git clone git@github.com:VectorInstitute/delirium-scorecard.git
  1. Navigate to the project frontend directory:
cd delirium-scorecard/frontend
  1. Install the dependencies:
npm install
  1. Run the frontend server in development mode:
npm run dev -- -p <port>
  1. Navigate to the repository root and install backend dependencies:
cd delirium-scorecard
poetry install
  1. Run the backend server:
uvicorn backend.api.main:app --reload --host 0.0.0.0 --port <port>
  1. Open your browser and visit http://localhost:<port> to see the application.

Project Structure

This project is divided into two main directories: frontend for the Next.js application and backend for the FastAPI server.

Frontend (Next.js)

frontend/
├── src/
│   ├── components/
│   │   ├── DeliriumRates.tsx
│   │   ├── TimeTrends.tsx
│   │   ├── PatientDemographics.tsx
│   │   ├── Sidebar.tsx
│   │   └── Layout.tsx
│   ├── app/
│   │   ├── page.tsx
│   │   ├── layout.tsx
│   │   ├── ThemeRegistry.tsx
│   │   ├── globals.css
│   │   └── faq/
│   │       ├── layout.tsx
│   │       ├── page.tsx
│   │       ├── error.tsx
│   │       └── loading.tsx
├── theme.ts
├── public/
│   └── images/
├── package.json
└── next.config.mjs
  • components/: Reusable React components
  • app/: Next.js pages and routing
  • public/: Static assets like images

Backend (FastAPI)

backend/
├── api/
│   ├── main.py
│   ├── routes.py
│   └── delirium.py

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the Apache 2.0 license.

Acknowledgements

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An application to predict delirium prevalence rates at hospitals

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