Team-2-dev is a responsive web application designed to streamline patient management and support clinicians with data-driven insights. Built as an MVP for a hackathon, this app features a main dashboard for patient data analysis and a specialized clinician dashboard to assist healthcare professionals in tracking, filtering, and querying patient data.
Key features include:
- Patient Search: A clinician-specific search tool for locating patients quickly.
- Data Visualization: Interactive charts for tracking patients seen over time and other critical metrics.
- Dynamic Filtering: Filter patients based on previous diagnoses and case studies for targeted analysis.
- Natural Language Querying: A natural language query section powered by OpenAI's API, allowing clinicians to retrieve insights using conversational language.
- Responsive Design: Optimized for both desktop and mobile devices.
- Interactive Charts: Visualize patient data trends over time, such as total patients seen, demographics, and more.
- Patient Search: Quickly search for patients within the system.
- Patient Data Filters: Filter by diagnoses, case studies, and other parameters for tailored insights.
- Additional Data Analytics: Various charts to analyze patient data, including case trends, recovery rates, and diagnostics.
- Natural Language Querying: Integrate OpenAI's API to answer clinician-specific questions about patient data.
Ensure you have the following installed:
- Node.js: To run the Next.js application.
- npm or yarn: For package management.
- OpenAI API Key: For enabling the natural language query feature.
- Clone the repository:
git clone https://github.com/your-username/Team-2-dev.git
- Navigate to the project directory:
cd Team-2-dev - Install dependencies:
npm install # or yarn install
- Create a
.env.localfile in the root of the project. - Add the following variables:
OPENAI_API_KEY=your_openai_api_key NEXT_PUBLIC_API_BASE_URL=http://localhost:3000/api
To start the development server, run:
npm run dev
# or
yarn devVisit http://localhost:3000 in your browser to access the app.
To create an optimized production build, run:
npm run build
# or
yarn buildThen start the application:
npm start
# or
yarn startThe main dashboard provides a responsive interface with charts displaying key patient statistics, including:
- Patients Seen Over Time: A line chart showing the number of patients seen.
- Patient Demographics: Demographic breakdowns of patients.
The clinician dashboard includes the following:
- Patient Search: Use keywords to quickly locate a patient's records.
- Dynamic Filters: Filter patients based on specific diagnoses or case studies.
- Natural Language Query: Input queries in natural language to analyze data (e.g., “Show me all patients diagnosed with diabetes”).
- Frontend: Next.js, React, CSS
- Backend: Node.js, Express.js
- Database: (e.g., MongoDB) [To be determined based on requirements]
- API Integration: OpenAI API for natural language querying
- Additional Visualizations: Expand chart options for deeper analysis.
- User Authentication: Secure access for clinicians.
- Role-Based Access: Differentiate access levels for clinicians and administrators.
- AI-Driven Insights: Integrate predictive analysis for identifying trends in patient health data.
- @1 - UI/UX, Next.js Development, Predictive Analysis Features
- @2 - Backend API, Database Integration
- @3 - Data Visualization, Chart Implementation
- @4 - Natural Language Query Integration
- @5 - Natural Language Query Integration
- @6 - Natural Language Query Integration
This project is licensed under the MIT License.
Special thanks to the hackathon organizers and OpenAI for API access.