Evidence map›Paper›PMID 38130791›Full record

ReviewWorld journal of clinical cases2023

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

Abstract readReview
In one paragraph

Review in World journal of clinical cases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Multichannel machine learning for polysomnographic diagnosis of obstructive sleep apnea: a Bayesian meta-analysis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Pooled it
  2. Article
  3. Article
  4. Artificial intelligence in sleep medicine: assessing the diagnostic precision of ChatGPT-4.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  5. Artificial intelligence may fill the gap of underdiagnosis in sleep medicine: the role of ChatGPT-4.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  6. Review
  7. Article
  8. A case study on generative artificial intelligence to extract the fundamental sleep parameters from polysomnography notes.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  9. Review
  10. Article
  11. [Sleep Innovation].Open respiratory archives · 2024
    Review
  12. Does the severity of obstructive sleep apnea increase the risk of cancer? Clues in apnea-hypopnea index and biomarkers.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Article
  13. Article
  14. Review
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ram Kishun VermaDepartment of Sleep Medicine, Parkview Health System, Fort Wayne, IN 46845, United States.
Gagandeep DhillonDepartment of Medicine, UM Baltimore Washington Medical Center, Glen Burnie, MD 21061, United States.
Harpreet GrewalDepartment of Radiology, Ascension Sacred Heart Hospital, Pensacola, FL 32504, United States.
Vinita PrasadDepartment of Psychiatry, Parkview Health System, Fort Wayne, IN 46845, United States.
Ripudaman Singh MunjalDepartment of Medicine, Kaiser Permanente Medical Center, Modesto, CA 95356, United States.
Pranjal SharmaDepartment of Medicine, Banner Health, Phoenix, AZ 85006, United States.
Venkata BuddhavarapuDepartment of Medicine, Norteast Ohio Medical University, Rootstown, OH 44272, United States.
Ramprakash DevadossDepartment of Cardiology, Carle Methodist Medical Center, Peroria, IL 61637, United States.
Rahul KashyapDepartment of Research, Wellspan Health, York, PA 17403, United States.
Salim SuraniDepartment of Medicine & Pharmacology, Texas A&M University, College Station, TX 77843, United States. srsurani@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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,

Indexed as

Artificial intelligenceDeep learningEthicalLegal, and sleep disordersMachine learning

Identifiers

PMID38130791
PMCPMC10731177

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.