Evidence map›Paper›PMID 37394867›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2023

Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

Anuja Bandyopadhyay, Charles Bae, Hao Cheng, Ambrose Chiang, Maryann Deak, Azizi Seixas, Jaspal Singh

Open access · greenAbstract read
In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 33% of its field
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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. OSA diagnosis goes wearable: are the latest devices ready to shine?Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Review
  3. Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: a commentary.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Review
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

7 authors at 6 institutions in 1 country.

Anuja BandyopadhyayDepartment of Pediatrics, Indiana University School of Medicine, Indianapolis, Indiana.
Charles BaeDivision of Sleep Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
Hao ChengDepartment of Pulmonary and Sleep Medicine, Miami VA Healthcare System, Miami, Florida.
Ambrose ChiangLouis Stokes Cleveland VA Medical Center, Case Western Reserve University, Cleveland, Ohio.
Maryann DeakeviCore healthcare, Boston, Massachusetts.
Azizi SeixasDepartment of Informatics and Health Data Science, University of Miami Miller School of Medicine, Coral Gables, Florida.
Jaspal SinghAtrium Health Department of Medicine, Wake Forest School of Medicine, Charlotte, North Carolina.
Case Western Reserve University · USIndiana University – Purdue University Indianapolis · USMiami VA Healthcare System · USUniversity of Miami · USUniversity of Pennsylvania · USWake Forest University · US

Funding

Promoting Academic Workforce Development in Behavioral Medicine and Sleep Disorders ResearchR25HL105444 · NHLBI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Girardin Jean-Louis, Tatjana Rundek · 2010 to 2026
$5.8M
DORMIR: Determinants, Outcomes, Responses and Markers of Insufficient sleep in Rural-Urban settingsR01HL152453 · NHLBI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI SEIXAS, AZIZI · 2020 to 2024
$3.7M
Personalized OSA treatment and effects on AD biomarkers and cognition among blacksR01AG075007 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI Girardin Jean-Louis, Azizi Seixas · 2022 to 2026
$3.0M
NHLBI NIH HHS R01 HL152453NHLBI NIH HHS R25 HL105444NIA NIH HHS R01 AG075007
6 · The paper itself

Abstract

Since the publication of its 2020 position statement on artificial intelligence (AI) in sleep medicine by the American Academy of Sleep Medicine, there has been a tremendous expansion of AI-related software and hardware options for sleep clinicians. To help clinicians understand the current state of AI and sleep medicine, and to further enable these solutions to be adopted into clinical practice, a discussion panel was conducted on June 7, 2022, at the Associated Professional Sleep Societies Sleep Conference in Charlotte, North Carolina. The article is a summary of key discussion points from this session, including aspects of considerations for the clinician in evaluating AI-enabled solutions including but not limited to what steps might be taken both by the Food and Drug Administration and clinicians to protect patients, logistical issues, technical challenges, billing and compliance considerations, education and training considerations, and other unique challenges specific to AI-enabled solutions. Our summary of this session is meant to support clinicians in efforts to assist in the clinical care of patients with sleep disorders utilizing AI-enabled solutions. CITATION: Bandyopadhyay A, Bae C, Cheng H, et al. Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

Indexed as

Artificial IntelligencePhysiciansHumansSleepSocieties, MedicalSoftwareUnited StatesAI-enabled solutionsartificial intelligenceclinical sleep medicinemachine learning

Identifiers

PMID37394867
PMCPMC10545999
OpenAlexW4382919382

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.