IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-031-68263-6_1.html
   My bibliography  Save this book chapter

Empowering Sleep Health: Unleashing the Potential of Artificial Intelligence and Data Science in Sleep Disorders

In: Handbook of AI and Data Sciences for Sleep Disorders

Author

Listed:
  • Xin Zan

    (University of Iowa)

  • Feng Liu

    (Stevens Institute of Technology)

  • Xiaochen Xian

    (Georgia Institute of Technology)

  • Panos M. Pardalos

    (University of Florida)

Abstract

Sleep health, a vital component of human well-being, is often overlooked in today’s fast-paced world, leading to a surge in the prevalence of sleep disorders that affect a large global population. Sleep disorders have emerged as a pressing health concern that not only causes significant adverse impacts on patients’ health and quality of life but also places a substantial economic burden on society. The advent of the fourth industrial revolution marks the onset of a new era in sleep health, characterized by the convergence of digital technologies and unprecedented access to data related to sleep disorders. Artificial Intelligence (AI) and Data Science (DS), two pillars of this technological revolution, are poised to unleash their transformative power in the multifaceted realm of sleep disorders. The synergy of AI and DS represents a transformative opportunity to not only unravel the complex tapestry of sleep disorders but also to illuminate the path toward more precise diagnosis, personalized treatment strategies, and a deeper understanding of sleep disorders, ultimately empowering sleep health. This chapter provides an extensive review of recent advancements in the applications and methodologies of AI and DS in sleep disorders from a multitude of perspectives.

Suggested Citation

  • Xin Zan & Feng Liu & Xiaochen Xian & Panos M. Pardalos, 2024. "Empowering Sleep Health: Unleashing the Potential of Artificial Intelligence and Data Science in Sleep Disorders," Springer Optimization and Its Applications, in: Richard B. Berry & Panos M. Pardalos & Xiaochen Xian (ed.), Handbook of AI and Data Sciences for Sleep Disorders, pages 1-44, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-68263-6_1
    DOI: 10.1007/978-3-031-68263-6_1
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:spochp:978-3-031-68263-6_1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.