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Accuracy of AI Laryngeal Disorder Detection
Review of 88 studies found AI systems achieved high accuracy for identifying abnormal voices, but performance declined among higher-level laryngeal disorder classifications.
AI systems show high accuracy in detecting abnormal voices but lower performance in identifying specific laryngeal disorders.
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Reported accuracies for distinguishing healthy from pathologic voices ranged from 88% to 99%, while specific disorder identification remained below 75%.
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The review analyzed 88 studies evaluating AI approaches for laryngeal disorder detection, highlighting a decline in performance from detection to diagnosis.
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Methodologic concerns included reliance on limited databases and sustained-vowel recordings, affecting the generalizability of AI performance.
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Current evidence supports AI as a tool for screening and monitoring, but it cannot replace endoscopic assessment for specific diagnoses.
