Proceedings ArticleDOI
A Remote Diagnostic System using Deep Learning Network for Heart Disease Detection
Thanh-Nghia Nguyen,Thanh-Hai Nguyen,Thanh-Tam Nguyen +2 more
- pp 274-278
TLDR
In this paper, a remote diagnostic system for heart disease via a server is proposed, where a patient's ECG signals are collected from a machine and then sent to the server containing a heart disease classification system using the deep learning network for classifying heart diseases.Abstract:
Nowadays, heart disease has very popularly affected human health. Early diagnosis of heart disease using deep learning networks is a significant task due to possible support for physicians. This paper proposed to build a remote diagnostic system for heart disease via a server. In particular, a patient’s ECG signals are collected from a machine and then sent to the server containing a heart disease classification system using the deep learning network for classifying heart diseases. Furthermore, this real system was designed with a suitable ECG data transmission protocol so that physicians can access the ECG signals and classification results using a smartphone or remote computer. The results obtained from the real experiments in the BME Lab showed that the proposed system operated stably and it can be developed to implement in diagnostic centers or hospitals.read more
Citations
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Journal ArticleDOI
Homecare-Oriented ECG Diagnosis With Large-Scale Deep Neural Network for Continuous Monitoring on Embedded Devices
TL;DR: To achieve diagnosing a wide range of cardiac diseases and continuous monitoring, a homecare-oriented ECG diagnosis platform is designed based on a large-scale multilabel deep conventional neural network.
Proceedings ArticleDOI
A Research Review on Fetal Heart Disease Detection Techniques
TL;DR: In this article , a meta-heuristic technique is proposed to choose salient aspects of the fetal heart disease (FHD) data to improve feature selection and reduce the number of risk features.
References
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