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Research Article
Sleeping Disorders Classification Using Machine Learning
Usharani. K1
Thendral Devi. K2
Vallimayil. P3
Varsha. K. S4
1Assistant Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering and Technology, Sivagangai, Tamilnadu, India. 2,3,4Student, Department of Computer Science and Engineering, K.L.N. College of Engineering and Technology, Sivagangai, Tamilnadu, India.
Published Online: September-October 2024
Pages: 19-21
Cite this article
No DOIReferences
[1]. Talal Sarheed Alshammari (2024). Applying Machine Learning Algorithms for the Classification of Sleep Disorders. IEEE Access,
12, 36110 - 36121
[2]. Mostafa M. Moussa,Ahsan H. Khandoker.(2022). Explainable ComputerAided Detection of Obstructive Sleep Apnea and
Depression.IEEE Access, 10, 110916 - 110933
[3]. Guangxin Zhou, Wenli Zhou, Yi Zhang, Zijing Zeng, Wei Zhao (2023). Automatic monitoring of obstructive sleep apnea based on
multimodal signals by phone and smartwatch, IEEE Access, 2375-7477
[4]. Meng Jiao, ShihaoYang,FengLiu,XiaochenXian,Changyue Song (2024). Deep Attention Networks with MultiTemporal Information
Fusion for Sleep Apnea Detection, IEEE Access, 1-11
12, 36110 - 36121
[2]. Mostafa M. Moussa,Ahsan H. Khandoker.(2022). Explainable ComputerAided Detection of Obstructive Sleep Apnea and
Depression.IEEE Access, 10, 110916 - 110933
[3]. Guangxin Zhou, Wenli Zhou, Yi Zhang, Zijing Zeng, Wei Zhao (2023). Automatic monitoring of obstructive sleep apnea based on
multimodal signals by phone and smartwatch, IEEE Access, 2375-7477
[4]. Meng Jiao, ShihaoYang,FengLiu,XiaochenXian,Changyue Song (2024). Deep Attention Networks with MultiTemporal Information
Fusion for Sleep Apnea Detection, IEEE Access, 1-11
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