Opinion Review
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Dec 6, 2023; 11(34): 8106-8110
Published online Dec 6, 2023. doi: 10.12998/wjcc.v11.i34.8106
Artificial intelligence in sleep medicine: Present and future
Ram Kishun Verma, Gagandeep Dhillon, Harpreet Grewal, Vinita Prasad, Ripudaman Singh Munjal, Pranjal Sharma, Venkata Buddhavarapu, Ramprakash Devadoss, Rahul Kashyap, Salim Surani
Ram Kishun Verma, Department of Sleep Medicine, Parkview Health System, Fort Wayne, IN 46845, United States
Gagandeep Dhillon, Department of Medicine, UM Baltimore Washington Medical Center, Glen Burnie, MD 21061, United States
Harpreet Grewal, Department of Radiology, Ascension Sacred Heart Hospital, Pensacola, FL 32504, United States
Vinita Prasad, Department of Psychiatry, Parkview Health System, Fort Wayne, IN 46845, United States
Ripudaman Singh Munjal, Department of Medicine, Kaiser Permanente Medical Center, Modesto, CA 95356, United States
Pranjal Sharma, Department of Medicine, Banner Health, Phoenix, AZ 85006, United States
Venkata Buddhavarapu, Department of Medicine, Norteast Ohio Medical University, Rootstown, OH 44272, United States
Ramprakash Devadoss, Department of Cardiology, Carle Methodist Medical Center, Peroria, IL 61637, United States
Rahul Kashyap, Department of Research, Wellspan Health, York, PA 17403, United States
Salim Surani, Department of Medicine & Pharmacology, Texas A&M University, College Station, TX 77843, United States
Author contributions: Verma RK involved in the initial draft, and literature search; Dhillon G, Sharma P, Kashyap R, and Surani S contributed to the revision of drafting; Dhillon G involved in the idea of the manuscript; Verma RK, Grewal H, Munjal RS, Devadoss R, and Surani S took part in the conceptualization of the article; Grewal H and Prasad V wrote the manuscript; Prasad V, Sharma P, Buddhavarapu V, Kashyap R, and Surani S edited the manuscript; Munjal RS contributed to the visualization of this study; Buddhavarapu V reviewed the manuscript; Kashyap R and Surani S contributed to the supervision of this study; Verma RK and Munjal RS designed the article.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Salim Surani, FCCP, MD, Professor, Department of Medicine & Pharmacology, Texas A&M University, 40 Bizzell Street, College Station, TX 77843, United States. srsurani@hotmail.com
Received: October 14, 2023
Peer-review started: October 14, 2023
First decision: November 2, 2023
Revised: November 3, 2023
Accepted: November 24, 2023
Article in press: November 24, 2023
Published online: December 6, 2023
Processing time: 52 Days and 8.5 Hours
Abstract

Artificial intelligence (AI) has impacted many areas of healthcare. AI in healthcare uses machine learning, deep learning, and natural language processing to analyze copious amounts of healthcare data and yield valuable outcomes. In the sleep medicine field, a large amount of physiological data is gathered compared to other branches of medicine. This field is primed for innovations with the help of AI. A good quality of sleep is crucial for optimal health. About one billion people are estimated to have obstructive sleep apnea worldwide, but it is difficult to diagnose and treat all the people with limited resources. Sleep apnea is one of the major contributors to poor health. Most of the sleep apnea patients remain undiagnosed. Those diagnosed with sleep apnea have difficulty getting it optimally treated due to several factors, and AI can help in this situation. AI can also help in the diagnosis and management of other sleep disorders such as insomnia, hypersomnia, parasomnia, narcolepsy, shift work sleep disorders, periodic leg movement disorders, etc. In this manuscript, we aim to address three critical issues about the use of AI in sleep medicine: (1) How can AI help in diagnosing and treating sleep disorders? (2) How can AI fill the gap in the care of sleep disorders? and (3) What are the ethical and legal considerations of using AI in sleep medicine?

Keywords: Artificial intelligence, Machine learning, Deep learning, Ethical, Legal, and sleep disorders

Core Tip: Most of the sleep apnea patients remain undiagnosed worldwide. Artificial intelligence can help alert people to be evaluated and seek treatment on time to improve overall health. Treatment of sleep apnea may improve or delay certain chronic illnesses.