Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: a commentary-Reference-Cited by-同舟云学术

Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: a commentary

Published:2024-07 Issue:7 Volume:20 Page:1183-1191
ISSN:1550-9389
Container-title:Journal of Clinical Sleep Medicine
language:en
Short-container-title:Journal of Clinical Sleep Medicine

Author:

Bandyopadhyay Anuja¹,Oks Margarita²,Sun Haoqi³,Prasad Bharati⁴,Rusk Sam⁵,Jefferson Felicia⁶,Malkani Roneil Gopal⁷⁸,Haghayegh Shahab⁹,Sachdeva Ramesh¹⁰,Hwang Dennis¹¹,Agustsson Jon¹²,Mignot Emmanuel¹³,Summers Michael¹⁴,Fabbri Daniel¹⁵,Deak Maryann¹⁶,Anastasi Matthew¹⁷,Sampson Andrew¹⁷,Van Hout Steve¹⁷,Seixas Azizi¹⁸

Affiliation:

1. Department of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana

2. Department of Medicine, Northwell Health System, New York, New York

3. Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts

4. Department of Medicine, University of Illinois, Chicago, Illinois

5. EnsoData Research, EnsoData, Madison, Wisconsin

6. Department of Biochemistry and Molecular Biology, University of Nevada, Reno, Nevada

7. Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois

8. Neurology Service, Jesse Brown Veterans Affairs Medical Center, Chicago, Illinois

9. Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts

10. Children’s Hospital of Michigan and Central Michigan University College of Medicine, Detroit, Michigan

11. Kaiser Permanente Southern California, Los Angeles, California

12. Nox Research, Nox Medical ehf, Reykjavik, Iceland

13. Stanford University, School of Medicine, Stanford, California

14. Division of Pulmonary, Critical Care, and Sleep Medicine, University of Nebraska Medical Center, Omaha, Nebraska

15. Vanderbilt University, Nashville, Tennessee

16. eviCore Healthcare, Boston, Massachusetts

17. American Academy of Sleep Medicine, Darien, Illinois

18. Department of Informatics and Health Data Science, University of Miami Miller School of Medicine, Miami, Florida

Publisher

American Academy of Sleep Medicine (AASM)

Reference51 articles.

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4. Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy

5. Brink-Kjaer A Gunter KM Mignot E During E Jennum P Sorensen HB . End-to-end deep learning of polysomnograms for classification of REM sleep behavior disorder. In: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Glasgow Scotland United Kingdom IEEE ; 2022 : 2941 – 2944 .