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What is Voiceprint and Machine Learning Models For Early Detection of Bulbar about?

This study presents a novel methodology for the early detection of bulbar dysfunction in amyotrophic lateral sclerosis (ALS) using voiceprint and machine learning models. The best-performing model achieved an accuracy of 91.0% in classifying bulbar versus non-bulbar patients, demonstrating the potential for automated diagnosis that surpasses traditional clinical methods. The findings suggest that this approach could lead to a cost-effective tool for early identification and monitoring of bulbar dysfunction

Author

Felipe Fontenele

Language

EN