ReviewWorld journal of otorhinolaryngology - head and neck surgery2026
Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions.
Review in World journal of otorhinolaryngology - head and neck surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods: Literature review. Conclusion: AI-based voice analysis is a promising tool for the screening and monitoring of vocal pathology, offering advantages in accessibility, scalability, and sensitivity to subtle acoustic features. However, current models remain limited by small data sets and lack of standardization in recording and reporting techniques. To move beyond proof-of-concept studies, future work must focus on longitudinal and multimodal data integration, explainability, fairness, and validated frameworks for implementation. Emerging strategies such as edge computing, synthetic data, and ambient electronic health record (EHR) integration may facilitate scalable, privacy-preserving adoption in clinical settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.