Ultrasound Predicts Drug‐Induced Sleep Endoscopy Findings Using Machine Learning Models

Authors

Natalie Aw
Molly Acord
Stephen M. Restaino (ORCID: https://orcid.org/0000-0003-2008-6107)
Danielle Sidelnikov (ORCID: https://orcid.org/0009-0007-7148-8428)
Sunny Haft (ORCID: https://orcid.org/0000-0002-7172-0035)
Samuel E. Jones (ORCID: https://orcid.org/0000-0003-4597-2033)
Sarah E. Miller (ORCID: https://orcid.org/0000-0001-9145-4398)

Institutions

University of Maryland, Baltimore (US)
Saint Agnes Hospital (US)
University of Maryland Medical Center (US)
Maryland Medical Research Institute (US)

Publication Details

Journal: The Laryngoscope
Published: 2025-01-29
DOI: https://doi.org/10.1002/lary.31950
Citations: 1
Primary Topic: Obstructive Sleep Apnea Research
Type: article
Field-Weighted Citation Impact: 1.16

Funders

Small Business Innovation Research

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article

Ultrasound Predicts Drug‐Induced Sleep Endoscopy Findings Using Machine Learning Models

Natalie Aw, Molly Acord, Stephen M. Restaino, Danielle Sidelnikov et al.

Jan 29, 2025

1 citations

The Laryngoscope

Obstructive Sleep Apnea Research

1.16

article

Ultrasound Predicts Drug‐Induced Sleep Endoscopy Findings Using Machine Learning Models

Natalie Aw, Molly Acord, Stephen M. Restaino, Danielle Sidelnikov, Sunny Haft, Samuel E. Jones, Sarah E. Miller

January 29, 2025article en

1 citations

Abstract

No abstract available for this paper.

The LaryngoscopeVol. 135(5)

University of Maryland, Baltimore (US), Saint Agnes Hospital (US), University of Maryland Medical Center (US), Maryland Medical Research Institute (US)

Small Business Innovation Research

Good health and well-being

Openalex Percentile: Top 26%

Obstructive Sleep Apnea Research

1.16

DOI Source OpenAlex

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