Obstructive Sleep Apnea Detection Scheme Based on Manually Generated Features and Parallel Heterogeneous Deep Learning Model Under IoMT-Reference-Cited by-同舟云学术

Obstructive Sleep Apnea Detection Scheme Based on Manually Generated Features and Parallel Heterogeneous Deep Learning Model Under IoMT

Author:

Shao Shiliang¹^ORCID,Han Guangjie²^ORCID,Wang Ting¹,Song Chunhe¹^ORCID,Yao Chen¹,Hou Jianxia³^ORCID

Affiliation:

1. State Key Laboratory of Robotics, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, China

2. Department of Internet of Things Engineering, Hohai University, Changzhou, China

3. Department of Periodontology, Peking University and Hospital of Stomatology, Beijing, China

Funder

Key Research and Development Program of Liaoning Province

National Key Research and Development Program of China

National Natural Science Foundation of China

Liaoning Province Doctoral Scientific Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

Reference47 articles.

5. Deep learning in bioinformatics;min;Brief Bioinf,2017

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