<?xml version="1.0"?>
<Articles JournalTitle="Journal of Sleep Sciences">
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Sleep Sciences</JournalTitle>
      <Issn>2476-2938</Issn>
      <Volume>6</Volume>
      <Issue>1-2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2022</Year>
        <Month>04</Month>
        <Day>19</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Deep Learning in Sleep Medicine: Advantages and Drawbacks</title>
    <FirstPage>51</FirstPage>
    <LastPage>52</LastPage>
    <AuthorList>
      <Author>
        <FirstName>Morteza</FirstName>
        <LastName>Zangeneh Soroush</LastName>
        <affiliation locale="en_US">Bio-intelligence Research Unit, Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2021</Year>
        <Month>05</Month>
        <Day>31</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2021</Year>
        <Month>07</Month>
        <Day>04</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Considering the advancements in machine learning, neural networks (NNs), as models of the human brain with the ability of generalization, have gained a great deal of attention in numerous fields of science such as sleep medicine for years (1). NNs have been widely used in sleep apnea detection, sleep stage recognition, audio-based snore detection, insomnia identification, detecting sleep-related movement disorder (SRMD), etc.</abstract>
    <web_url>https://jss.tums.ac.ir/index.php/jss/article/view/202</web_url>
  </Article>
</Articles>
