HealthCloud

HealthCloud: A System for Monitoring Health Status of Heart Patients using Machine Learning and Cloud Computing

Code for this project is accessible on Github

Features

• Prototype application for a mobile device for the user to use. This offers a visual display and automated response to the user of their chances of having heart disease.
• Built using the Logistic Regression Machine Learning model on the Cleveland Heart Disease from the UCI Machine Learning Repository, also available in the heart_data.csv file.
• The user can manually enter their medical data, which must be measured externally from the app, and with the help of Machine Learning the app will provide some advice to the user according to their results.
• Supported on iPhone, iPad and Mac devices.

How to use the application

1. Download or clone the repository:

git clone https://github.com/Forum-123/Predictive-Heart-Disease-Model.git
cd PredictiveHeartDiseaseApp

2. Open PredictiveHeartDiseaseApp.xcworkspace in Xcode.
3. Choose the device that you wish to run the application on.
4. Build the project & run either on a simulator or a physical device.

View Data Analysis

1. Download or clone the repository:

git clone https://github.com/Forum-123/Predictive-Heart-Disease-Model.git
cd Data Analysis

2. Open Data Exploration and Cleaning.ipynb for the Python code for data cleaning and Model Evaluation.ipynb for the Python code on training and evaluating Machine Learning models on Google Colaboratory or Anaconda (Jupyter).
3. To calculate memory usage, open Measuring Memory Usage.py and run python "Measuring Memory Usage.py".

Data

The original Heart Disease dataset can be downloaded from the UCI Machine Learning Repository's Heart Disease directory (processed.cleveland.data). Database Donor: David W. Aha (aha@ics.uci.edu) (714) 856-8779

Warning

The copyright of the shared work is reserved. Reference should be cite to the HealthCloud article for use in academic studies.

To cite (text)

Forum Desai, Deepraj Chowdhury, Rupinder Kaur, Marloes Peeters, Rajesh Chand Arya, Gurpreet Singh Wander, Sukhpal Singh Gill, Rajkumar Buyya, HealthCloud: A system for monitoring health status of heart patients using machine learning and cloud computing, Internet of Things, Volume 17, 2022, 100485, https://doi.org/10.1016/j.iot.2021.100485.

To cite (.bib)

@article{DESAI2022100485, title = {HealthCloud: A system for monitoring health status of heart patients using machine learning and cloud computing}, author={Desai, Forum and Chowdhury, Deepraj and Kaur, Rupinder and Peeters, Marloes and Arya, Rajesh Chand and Wander, Gurpreet Singh and Gill, Sukhpal Singh and Buyya, Rajkumar}, journal = {Internet of Things}, volume = {17}, pages = {100485}, year = {2022}, issn = {2542-6605}, doi = {https://doi.org/10.1016/j.iot.2021.100485 } }