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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (5177) Respiratory Medicine (216) Natural Language Processing (1297) Machine Learning (3204) ENT (Ear, Nose, Throat) (48) Digital Biomarkers and Digital Phenotyping (452) Computer-Aided Diagnosis (427) Voice Phenotyping and Vocal Biomarkers (34)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/86069, first published .
Doctor and patient reviewing voice waveform on tablet for voice therapy.

Prediction of Aspiration Risk by Using Vocal Biomarkers: Machine Learning Development and Validation Study

Prediction of Aspiration Risk by Using Vocal Biomarkers: Machine Learning Development and Validation Study

Authors of this article:

Cyril Varghese1 Author Orcid Image ;   Jianwei Zhang2 Author Orcid Image ;   Sara Charney3 Author Orcid Image ;   Abdelmohaymin A Abdalla1 Author Orcid Image ;   Elizabeth Reeves3 Author Orcid Image ;   Stacy Holyfield3 Author Orcid Image ;   Adam E Brown4 Author Orcid Image ;   Michelle K Higgins4 Author Orcid Image ;   Hunter Stearns4 Author Orcid Image ;   Julie Liss5 Author Orcid Image ;   Nan Zhang6 Author Orcid Image ;   Diana Orbelo7 Author Orcid Image ;   Rebecca L Pittelko7 Author Orcid Image ;   Lindsay Rigelman7 Author Orcid Image ;   Victor Ortega8 Author Orcid Image ;   David G Lott3 Author Orcid Image ;   Visar Berisha2 Author Orcid Image
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Journals

  1. Koo C, Herasevich V, Diedrich D, Brown D, Pickering B. Integrated rescue: A narrative review of machine learning in hospitalized patient rescue. Intensive Care Science 2026;1:49 View