USC_UCT_Cloud_Computing_Internship

Parkinson's Disease Detection using Cloud Computing

The primary objective of this project is to develop, validate, and implement a novel voice frequency-based predictive system for the early detection of Parkinson's disease, aiming to improve upon the limitations of existing typing speed-based systems. This system will employ ensemble modelling techniques to enhance prediction accuracy and sensitivity, offering a more comprehensive and user-friendly approach for Parkinson's disease screening. Additionally, the project seeks to address data privacy and ethical considerations, and it aims to provide a clinically validated tool for healthcare practitioners and researchers to assist in the early diagnosis of Parkinson's disease. Our project aspires to transform the landscape of early diagnosis by harmonizing diverse data sources and sculpting features that resonate with the subtleties of Parkinson's symptoms. The project leverages an ensemble of machine learning models to deliver a comprehensive predictive system that offers enhanced accuracy and sensitivity.

Steps to Run the Project:-

sudo apt update

sudo apt-get update

sudo apt upgrade -y

sudo apt install git curl unzip tar make sudo vim wget -y

git clone "Your-repository"

sudo apt install python3-pip

pip3 install -r requirements.txt

Permanent running

nohup python3 -m streamlit run parkinsons web app.py

Result Screenshots:

Deployment Link: https://ec2-13-201-77-221.ap-south-1.compute.amazonaws.com/

(We terminated the instance since it was running on t2.medium and had pay-as-you-go pricing.)