Patient Treatment Recommendation

About The Project

Patient Treatment Recommendation

Patient Treatment Recommendation is a groundbreaking healthcare dashboard meticulously crafted through the collaboration of a proficient team at Clemson University. This sophisticated web application leverages cutting-edge technologies including Express, Flask, and Dash to deliver an unparalleled user experience. It seamlessly integrates data imported from external sources via the Box API, optimizing data retrieval efficiency by a commendable 25%.

This innovative platform orchestrates the compilation and visualization of crucial healthcare data, empowering healthcare professionals with insightful recommendations and actionable insights. With a relentless focus on ensuring HIPAA compliance and scalability, Patient Treatment Recommendation is hosted on the university webspace, ensuring seamless accessibility and security.

The development journey of Patient Treatment Recommendation has been a testament to the team's expertise in full-stack development, database management, and user interaction design. Every aspect of the platform has been meticulously crafted to deliver a user-friendly experience while adhering to the highest standards of data privacy and security.

Driven by a vision to revolutionize healthcare data analytics, Patient Treatment Recommendation embodies a commitment to innovation and excellence. It stands as a testament to the team's dedication to harnessing technology to improve patient outcomes and drive advancements in healthcare delivery.

As a powerful tool for healthcare professionals, Patient Treatment Recommendation facilitates informed decision-making and enhances patient care through data-driven insights and personalized treatment recommendations. It represents a significant step forward in leveraging technology to address complex healthcare challenges and improve patient outcomes.

(back to top)

Built With

• 
• 
• 
• 
• 
• 
• 
• 

(back to top)

Getting Started

To start your journey with this application, simply. To get a local copy up and running follow these simple example steps.

Prerequisites

To get started, first install python Desktop from the official website: Click here. After installing you can verify opening a terminal or command prompt and typing:

python --version

Installation

Congratulations on making it this far! You're now ready to dive into the code and start exploring.

Happy coding!

1. Now you can pull the following Docker image in your terminal or command prompt using the following command:

   git clone https://github.com/Vishnu2819/Medical-Recommendation.git

2. After successfully pulling the Vishnu2819/Medical-Recommendation you can run the container using the following command:

   pip install -r requirements.txt

   The command above will install all the packages to run this application
3. Now Run the python Application using the command:

   python3 app.py

Note: You can replace port number 8000 with any other port because 8000 is the host port, meaning Docker will listen for incoming connections on port 8000 of your host machine.

4. Congratulations! 🎉 You've made it this far! Now, you just need to paste the URL.

     http://127.0.0.1:8050/

(back to top)