As the number of patients with cardiovascular diseases (CVDs) increases annually, a reliable and automated system for detecting electrocardiogram (ECG) abnormalities is becoming increasingly essential. Scholars have developed numerous methods of arrh...
This study introduces a novel integrated quantitative modeling framework to assess the multiple environmental, health, and economic benefits from implementing carbon capture technology in the power sector of Basra province, Iraq. This province is str...
BACKGROUND: Clostridioides difficile infection results in life-threatening short-term outcomes and the potential for subsequent recurrent infection. Predicting these outcomes at diagnosis, when important clinical decisions need to be made, has proven...
Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents nume...
The timely detection of falls and alerting medical aid is critical for health monitoring in elderly individuals living alone. This paper mainly focuses on issues such as poor adaptability, privacy infringement, and low recognition accuracy associated...
The aim of this study is to address the challenge of 12-lead ECG delineation by different encoder-decoder architectures of deep neural networks (DNNs). This study compares four concepts for encoder-decoders based on a fully convolutional architecture...
In current smart classroom research, numerous studies focus on recognizing hand-raising, but few analyze the movements to interpret students' intentions. This limitation hinders teachers from utilizing this information to enhance the effectiveness of...
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