Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic
| Main Authors: | Ioannis Dimitris Apostolopoulos, Bessiana Tzani |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2020
|
| Online Access: |
https://zenodo.org/record/3679316 |
Daftar Isi:
- Internet of Things is a field of growing interest and reputations. It is a result of the advances of computer science and electronics, which enable the researchers and industries to design and create devices that connect with each other and with the cloud to offer swift and significant services to individuals. In this work, we propose a novel application design for the prognosis of Coronary Artery Disease (CAD), which exploits the capabilities of IoT devices. We focus our work in the decision framework of the model, employing Artificial Neural Networks, Decision Trees, and Fuzzy Cognitive Maps. The inner architecture of the model is powered by the use of the Internet, to access patient data and updates. Its accuracy may be improved by taking advantage of heart rate signals, measured from wearable devices. The user is informed of the risk in several ways and is the one to monitor the functionality of the application through a graphical user interface (GUI).