Literature DB >> 32022674

Artificial intelligence in sleep medicine: an American Academy of Sleep Medicine position statement.

Cathy A Goldstein1, Richard B Berry2, David T Kent3, David A Kristo4, Azizi A Seixas5, Susan Redline6, M Brandon Westover7, Fariha Abbasi-Feinberg8, R Nisha Aurora9, Kelly A Carden10, Douglas B Kirsch11, Raman K Malhotra12, Jennifer L Martin13,14, Eric J Olson15, Kannan Ramar15, Carol L Rosen16, James A Rowley17, Anita V Shelgikar1.   

Abstract

None: Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.
© 2020 American Academy of Sleep Medicine.

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Year:  2020        PMID: 32022674      PMCID: PMC7161449          DOI: 10.5664/jcsm.8288

Source DB:  PubMed          Journal:  J Clin Sleep Med        ISSN: 1550-9389            Impact factor:   4.062


  8 in total

1.  The Respiratory Signature: A Novel Concept to Leverage Continuous Positive Airway Pressure Therapy as an Early Warning System for Exacerbations of Common Diseases such as Heart Failure.

Authors:  Christopher N Schmickl; Eric Heckman; Robert L Owens; Robert J Thomas
Journal:  J Clin Sleep Med       Date:  2019-06-15       Impact factor: 4.062

Review 2.  Phenotypic approaches to obstructive sleep apnoea - New pathways for targeted therapy.

Authors:  Danny J Eckert
Journal:  Sleep Med Rev       Date:  2016-12-18       Impact factor: 11.609

3.  Algorithmic Complexity of EEG for Prognosis of Neurodegeneration in Idiopathic Rapid Eye Movement Behavior Disorder (RBD).

Authors:  Giulio Ruffini; David Ibañez; Eleni Kroupi; Jean-François Gagnon; Jacques Montplaisir; Ronald B Postuma; Marta Castellano; Aureli Soria-Frisch
Journal:  Ann Biomed Eng       Date:  2018-08-30       Impact factor: 3.934

4.  Large-Scale Automated Sleep Staging.

Authors:  Haoqi Sun; Jian Jia; Balaji Goparaju; Guang-Bin Huang; Olga Sourina; Matt Travis Bianchi; M Brandon Westover
Journal:  Sleep       Date:  2017-10-01       Impact factor: 5.849

5.  An end-to-end framework for real-time automatic sleep stage classification.

Authors:  Amiya Patanaik; Ju Lynn Ong; Joshua J Gooley; Sonia Ancoli-Israel; Michael W L Chee
Journal:  Sleep       Date:  2018-05-01       Impact factor: 5.849

6.  Expert-level sleep scoring with deep neural networks.

Authors:  Siddharth Biswal; Haoqi Sun; Balaji Goparaju; M Brandon Westover; Jimeng Sun; Matt T Bianchi
Journal:  J Am Med Inform Assoc       Date:  2018-12-01       Impact factor: 4.497

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

Authors:  Jens B Stephansen; Alexander N Olesen; Mads Olsen; Aditya Ambati; Eileen B Leary; Hyatt E Moore; Oscar Carrillo; Ling Lin; Fang Han; Han Yan; Yun L Sun; Yves Dauvilliers; Sabine Scholz; Lucie Barateau; Birgit Hogl; Ambra Stefani; Seung Chul Hong; Tae Won Kim; Fabio Pizza; Giuseppe Plazzi; Stefano Vandi; Elena Antelmi; Dimitri Perrin; Samuel T Kuna; Paula K Schweitzer; Clete Kushida; Paul E Peppard; Helge B D Sorensen; Poul Jennum; Emmanuel Mignot
Journal:  Nat Commun       Date:  2018-12-06       Impact factor: 14.919

8.  Sleep Apnea Heterogeneity, Phenotypes, and Cardiovascular Risk. Implications for Trial Design and Precision Sleep Medicine.

Authors:  Andrey Zinchuk; H Klar Yaggi
Journal:  Am J Respir Crit Care Med       Date:  2019-08-15       Impact factor: 21.405

  8 in total
  11 in total

1.  Autopilot and algorithms: accidents, errors, and the current need for human oversight.

Authors:  Douglas Kirsch
Journal:  J Clin Sleep Med       Date:  2020-10-15       Impact factor: 4.062

2.  Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures.

Authors:  Daniel Álvarez; Gonzalo C Gutiérrez-Tobal; Fernando Vaquerizo-Villar; Fernando Moreno; Félix Del Campo; Roberto Hornero
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 3.650

3.  Artificial Intelligence Analysis of Mandibular Movements Enables Accurate Detection of Phasic Sleep Bruxism in OSA Patients: A Pilot Study.

Authors:  Jean-Benoit Martinot; Nhat-Nam Le-Dong; Valérie Cuthbert; Stéphane Denison; David Gozal; Gilles Lavigne; Jean-Louis Pépin
Journal:  Nat Sci Sleep       Date:  2021-08-23

4.  Performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea in a large sleep clinic cohort.

Authors:  Octavian C Ioachimescu; J Shirine Allam; Arash Samarghandi; Neesha Anand; Barry G Fields; Swapan A Dholakia; Saiprakash B Venkateshiah; Rina Eisenstein; Mary-Margaret Ciavatta; Nancy A Collop
Journal:  J Clin Sleep Med       Date:  2020-10-15       Impact factor: 4.062

5.  Designing a Clinical Education Tracking System: An Innovative Approach.

Authors:  Abdullah Alismail; Braden Michael Tabisula; David López
Journal:  Adv Med Educ Pract       Date:  2021-05-26

6.  Evaluating consumer and clinical sleep technologies: an American Academy of Sleep Medicine update.

Authors:  Sharon Schutte-Rodin; Maryann C Deak; Seema Khosla; Cathy A Goldstein; Michael Yurcheshen; Ambrose Chiang; Dominic Gault; Joseph Kern; Daniel O'Hearn; Scott Ryals; Nitun Verma; Douglas B Kirsch; Kelly Baron; Steven Holfinger; Jennifer Miller; Ruchir Patel; Sumit Bhargava; Kannan Ramar
Journal:  J Clin Sleep Med       Date:  2021-11-01       Impact factor: 4.062

7.  Sleep and Big Data: harnessing data, technology, and analytics for monitoring sleep and improving diagnostics, prediction, and interventions-an era for Sleep-Omics?

Authors:  Susan Redline; Shaun M Purcell
Journal:  Sleep       Date:  2021-06-11       Impact factor: 6.313

8.  Improving the performance of peripheral arterial tonometry-based testing for the diagnosis of obstructive sleep apnea.

Authors:  Octavian C Ioachimescu; Swapan A Dholakia; Saiprakash B Venkateshiah; Barry Fields; Arash Samarghandi; Neesha Anand; Rina Eisenstein; Mary-Margaret Ciavatta; J Shirine Allam; Nancy A Collop
Journal:  J Investig Med       Date:  2020-09-07       Impact factor: 2.895

9.  Artificial intelligence in the practice of pulmonology: The future is now.

Authors:  Nishant Kumar Chauhan; Shahir Asfahan; Naveen Dutt; Ram Niwas Jalandra
Journal:  Lung India       Date:  2022 Jan-Feb

10.  Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study.

Authors:  Satoru Tsuiki; Takuya Nagaoka; Tatsuya Fukuda; Yuki Sakamoto; Fernanda R Almeida; Hideaki Nakayama; Yuichi Inoue; Hiroki Enno
Journal:  Sleep Breath       Date:  2021-02-08       Impact factor: 2.816

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