典型文献
A comprehensive review of approaches to detect fatigue using machine learning techniques
文献摘要：
In the past decades, there have been numerous advancements in the field of technology. This has led to many scientific breakthroughs in the field of medical sciences. In this, rapidly transforming world we are having a difficult time and the problem of fatigue is becoming prevalent. So, this study aimed to understand what is fatigue, its repercussions, and techniques to detect it using machine learning (ML) approaches. This paper introduces, discusses methods and recent advancements in the field of fatigue detection. Further, we categorized the methods that can be used to detect fatigue into four diverse groups, that is, mathematical models, rule-based implementation, ML, and deep learning. This study presents, compares, and contrasts various algorithms to find the most promising approach that can be used for the detection of fatigue. Finally, the paper discusses the possible areas for improvement.
文献关键词：
deep learning;driver monitoring;fatigue detection;healthcare;machine learning
中图分类号：
作者姓名：
Hooda Rohit;Joshi Vedant;Shah Manan
作者机构：
Gandhinagar Institute of Technology, Gujarat Technological University, Gandhinagar, Gujarat, India;LJ Institute of Engineering and Technology, Gujarat Technological University, Ahmedabad, Gujarat, India;Department of Chemical Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India
文献出处：
引用格式：
[1]Hooda Rohit;Joshi Vedant;Shah Manan-.A comprehensive review of approaches to detect fatigue using machine learning techniques)[J].慢性疾病与转化医学（英文）,2022(01):26-35
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AB值：
0.580355
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