Automatic detection of vocal cord disorders using machine learning method for healthcare system
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-022-01761-8.pdf
Reference24 articles.
1. Akshay S, Vincent K (2019) Identification of parkinson disease patients classification using feed forward technique based on speech signals. Int J Eng Adv Technol IJEAT 8(5):1769–1778
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3. Alsulaiman M (2014) Voice pathology assessment systems for dysphonic patients: detection, classification, and speech recognition. IETE J Res 60(2):156–167
4. Basheer S, Anbarasi M, Sakshi DG et al (2020) Efficient text summarization method for blind people using text mining techniques. Int J Speech Technol 23:713–725. https://doi.org/10.1007/s10772-020-09712-z
5. Behroozmand R, Almasganj F (2007) Optimal selection of wavelet-packet-based features using genetic algorithm in pathological assessment of patients’ speech signal with unilateral vocal fold paralysis. Comput Biol Med 37(4):474–485. https://doi.org/10.1016/j.compbiomed.2006.08.016
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