https://github.com/abdul-wahab619/ai-medlab
AI-based medical laboratory is a project that aims to use artificial intelligence (AI), machine learning (ML) to improve the quality and efficiency of laboratory medicine. There are three modules like customer or local person, doctor and lab assistant. This project we built in MERN Stack.
https://github.com/abdul-wahab619/ai-medlab
abdulwahab ai-medical ai-medlab ai-ml expressjs final-year-project final-year-project-code full-stack-web-development fyp github mern-stack mongodb nodejs reactjs
Last synced: 3 months ago
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AI-based medical laboratory is a project that aims to use artificial intelligence (AI), machine learning (ML) to improve the quality and efficiency of laboratory medicine. There are three modules like customer or local person, doctor and lab assistant. This project we built in MERN Stack.
- Host: GitHub
- URL: https://github.com/abdul-wahab619/ai-medlab
- Owner: abdul-wahab619
- License: mit
- Created: 2024-02-15T06:23:01.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-23T09:16:20.000Z (10 months ago)
- Last Synced: 2024-07-23T11:11:16.833Z (10 months ago)
- Topics: abdulwahab, ai-medical, ai-medlab, ai-ml, expressjs, final-year-project, final-year-project-code, full-stack-web-development, fyp, github, mern-stack, mongodb, nodejs, reactjs
- Language: JavaScript
- Homepage: https://linktr.ee/mr.abdulwahab.aw
- Size: 51.8 MB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
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README
# AI-based Medical Laboratory
## Project Overview
The AI-based Medical Laboratory project aims to revolutionize laboratory medicine through the use of artificial intelligence (AI) and machine learning (ML). By enhancing the precision and speed of laboratory processes, the project seeks to reduce human errors, cut costs, and ultimately improve patient outcomes and satisfaction.
### Features
- **Customer Module**: Allows patients to submit samples and receive results.
- **Doctor Module**: Provides doctors with tools to analyze lab results and make informed decisions.
- **Lab Assistant Module**: Assists lab technicians with managing samples and running analyses using AI/ML tools.
### Pros and Cons
#### Pros
- Enhances precision and speed of laboratory medicine.
- Reduces human errors and operational costs.
- Improves patient outcomes and satisfaction.
#### Cons
- Challenges with data quality and availability.
- Requires significant computing power.
- Issues of trust, acceptance, and the need for education.
### Technologies Used
- **Frontend**: React, Redux, HTML, CSS, JavaScript
- **Backend**: Node.js, Express, MongoDB
- **AI/ML Tools**: Python, R, TensorFlow, PyTorch, scikit-learn, pandas, NumPy, matplotlib, seaborn
## Project Structure
The project is structured into two main directories:
- `frontend`: Contains the frontend code built with React.
- `backend`: Contains the backend code built with Node.js and Express.
## Installation
### Prerequisites
- Node.js and npm installed on your machine.
- MongoDB installed and running.
### Steps
1. **Clone the repository**
```bash
git clone https://github.com/your-username/ai-medical-lab.git
cd ai-medical-lab
```
2. **Install dependencies for backend**
```bash
cd backend
npm install
```
3. **Install dependencies for frontend**
```bash
cd ../frontend
npm install
```
4. **Set up environment variables**
- Create a `.env` file in the `backend` directory and add the following:
```text
MONGO_URI=your_mongodb_uri
PORT=5000
```
5. **Run the backend server**
```bash
cd ../backend
npm start or nodemon
```
6. **Run the frontend server**
```bash
cd ../frontend
npm start
```
## Usage
- Access the application at `http://localhost:5173`.
- Use the frontend interface to interact with the different modules (Customer, Doctor, Lab Assistant).
## Contributors
- **[Abdul Wahab](https://github.com/abdul-wahab619)** - Full Stack Developer
- **[Nafeesa Shehzadi](https://github.com/nafeesa-shehzadi)** - Frontend Developer
## Collaboration
We welcome contributions from everyone! If you are interested in contributing to this project, please follow these steps:
1. Fork the repository.
2. Create a new branch (`git checkout -b feature-branch`).
3. Make your changes.
4. Commit your changes (`git commit -m 'Add new feature'`).
5. Push to the branch (`git push origin feature-branch`).
6. Create a Pull Request.
For major changes, please open an issue first to discuss what you would like to change.
Feel free to reach out to us with any questions or suggestions. Let's collaborate to extend the exposure and impact of this project!
## License
This project is licensed under the [MIT License](https://github.com/abdul-wahab619/AI-MedLab/blob/main/LICENSE).