A Comparative Study on Cloud-based and Edge-Based Digital Twin Frameworks for Prediction of Cardiovascular Disease

Havvanur Dervişoğlu, Burak Ülver, Rabia Yurtoğlu, Ruşen Halepmollası, Mehmet Haklıdır

2023

Abstract

Digital Twins that can integrate with related technologies such as Artificial intelligence, optimization, mobile communication systems, edge computing, fog computing, cloud computing, etc. are virtual representations of physical objects and reflect the real time status through streaming data. In this study, we provide two Digital Twin frameworks both cloud-based and edge-based and compare them in terms of scalability, flexibility, latency and security. We represented those frameworks by developing a case study to predict cardiac patient, continuously monitor the risks related to heart disease, and reporting the risks to both healthcare professionals and users in real time. We extracted features over electrocardiogram signals and performed popular machine learning algorithms. We employed feature binning and feature selection methods to increase the robustness of the prediction model and, in total, we built 20 models. We presented empirical analysis on a publicly available dataset based on PTB Diagnostic ECG Database and evaluated the results in terms of accuracy, precision, recall and F-score. When predicting cardiac patients, Linear Regression outperformed the other classifiers with accuracy and F-score rates of 86% and 92%, respectively. This model has also the highest recall rate (98%), which is vital in predicting diseases. Meanwhile, Gradient Boosted Tree applied binning, mRMR feature selection method and random oversampling achieve high precision (91%).

Paper Citation

in Harvard Style

Dervişoğlu H., Ülver B., Yurtoğlu R., Halepmollası R. and Haklıdır M. (2023). A Comparative Study on Cloud-based and Edge-Based Digital Twin Frameworks for Prediction of Cardiovascular Disease. In Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-645-3, SciTePress, pages 159-169. DOI: 10.5220/0011859400003476

in Bibtex Style

@conference{ict4awe23,
author={Havvanur Dervişoğlu and Burak Ülver and Rabia Yurtoğlu and Ruşen Halepmollası and Mehmet Haklıdır},
title={A Comparative Study on Cloud-based and Edge-Based Digital Twin Frameworks for Prediction of Cardiovascular Disease},
booktitle={Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2023},
pages={159-169},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011859400003476},
isbn={978-989-758-645-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - A Comparative Study on Cloud-based and Edge-Based Digital Twin Frameworks for Prediction of Cardiovascular Disease
SN - 978-989-758-645-3
AU - Dervişoğlu H.
AU - Ülver B.
AU - Yurtoğlu R.
AU - Halepmollası R.
AU - Haklıdır M.
PY - 2023
SP - 159
EP - 169
DO - 10.5220/0011859400003476
PB - SciTePress