BiGRU-ANN based hybrid architecture for intensified classification tasks with explainable AI

Chakraborty, Sovon; Talukder, Muhammad Borhan Uddin; Hasan, Mohammad Mehadi; Noor, Jannatun; Uddin, Jia

doi:10.1007/s41870-023-01515-0

Cited by 7 publications

(1 citation statement)

References 32 publications

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“…Electrocardiogram (ECG) signals provide a detailed understanding of heart conditions by analyzing physiological signals [4], [5]. Thanks to technological advancements, ECG signals can now be accurately measured and observed using ECG monitoring devices [6], [7]. Despite the availability of ECG monitoring devices, analyzing the data obtained from them remains a major concern for researchers.…”

Section: Introductionmentioning

confidence: 99%

A cost-effective ECG monitoring in rural areas: leveraging artificial neural networks for efficient healthcare solutions

Rahaman,

Kashem

2024

Bulletin EEI

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Cardiovascular diseases engender serious public health concerns in developing nations since access to specialized medical equipment is often limited and standard treatment expenses can be prohibitive. This study proposes an efficient and relatively affordable electrocardiogram (ECG) monitoring system that reads and analyzes a person's electrocardiogram data to provide affordable and quality healthcare solutions. The device initially extracts features from electrocardiogram records by reading electrical signals in the heart. Extracted data are then analyzed by a trained deep learning model to determine precisely if the heart is in a healthy state or undergoing complexities. Experimental results showed that the fine-tuned ANN architecture outperformed the state-of-the-art architectures in this field with an accuracy of 98.95%. The data can also be sent to specialists through an MQTT server if necessary, allowing for remote diagnosis and treatment. The system is intended to be deployed in countries where rural regions lack access to specialized healthcare equipment and professionals. Additionally, the device is inexpensive and, hence can be made accessible to people with limited affordability.

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