New developments in the application of artificial intelligence to laryngology.
| Autor: | Torborg SR; Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine.; Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program, New York, New York, USA., Kim AYE; Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine., Rameau A; Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine. |
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| Jazyk: | angličtina |
| Zdroj: | Current opinion in otolaryngology & head and neck surgery [Curr Opin Otolaryngol Head Neck Surg] 2024 Dec 01; Vol. 32 (6), pp. 391-397. Date of Electronic Publication: 2024 Jul 24. |
| DOI: | 10.1097/MOO.0000000000000999 |
| Abstrakt: | Purpose of Review: The purpose of this review is to summarize the existing literature on artificial intelligence technology utilization in laryngology, highlighting recent advances and current barriers to implementation. Recent Findings: The volume of publications studying applications of artificial intelligence in laryngology has rapidly increased, demonstrating a strong interest in utilizing this technology. Vocal biomarkers for disease screening, deep learning analysis of videolaryngoscopy for lesion identification, and auto-segmentation of videofluoroscopy for detection of aspiration are a few of the new ways in which artificial intelligence is poised to transform clinical care in laryngology. Increasing collaboration is ongoing to establish guidelines and standards for the field to ensure generalizability. Summary: Artificial intelligence tools have the potential to greatly advance laryngology care by creating novel screening methods, improving how data-heavy diagnostics of laryngology are analyzed, and standardizing outcome measures. However, physician and patient trust in artificial intelligence must improve for the technology to be successfully implemented. Additionally, most existing studies lack large and diverse datasets, external validation, and consistent ground-truth references necessary to produce generalizable results. Collaborative, large-scale studies will fuel technological innovation and bring artificial intelligence to the forefront of patient care in laryngology. (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.) |
| Databáze: | MEDLINE |
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