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A novel solution of deep learning for sleep apnea detection: enhancement of SC and elimination of GVICS |
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| Authors: | Limbu Narayan Alsadoon Abeer Prasad PWC Abdullah Salma Rashid Tarik A Alsadoon Omar Hisham Jerew Oday D Alrubaie Ahmad |
| Affiliation: | 1.School of Computing Mathematics and Engineering, Charles Sturt University (CSU), Wagga Wagga, Australia ;2.School of Computer Data and Mathematical Sciences, Western Sydney University (WSU), Sydney, Australia ;3.Kent Institute Australia, Sydney, Australia ;4.Asia Pacific International College (APIC), Sydney, Australia ;5.Department of Computer Engineering, University of Technology, Baghdad, Iraq ;6.Computer Science and Engineering, University of Kurdistan Hewler, Erbil, KRG, Iraq ;7.Department of Islamic Sciences, Al Iraqia University, Baghdad, Iraq ;8.Faculty of Medicine, University of New South Wales, Sydney, Australia ; |
| Abstract: | Multimedia Tools and Applications - Convolutional neural network (CNN) classification has not achieved a medically-satisfied level of accuracy in sleep apnea detection due to the negative effect of... |
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