Robust Neurodegenerative Disease Detection Using Machine Learning Algorithms

Author:

Mahendran Kirann,Yadav Vedant,Mishra Shamik,Vardharajan Prathiksha,Kulkarni Subhash S.

Publisher

Springer Nature Switzerland

Reference16 articles.

1. Tsanas, A., Little, M., McSharry, P., Ramig, L.: Accurate telemonitoring of Parkinson’s disease progression by noninvasivespeech tests. IEEE Trans. Bio-Med. Eng. (2009)

2. Tsanas, A., Little, M., Mcsharry, P.E., Ramig, L.: Robust parsimonious selection of dysphonia measures for telemonitoring of Parkinson’s disease symptom severity. In: Seventh International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications MAVEBA (2011)

3. MohamedShreif, H.O., Lawgali, A.: Speech recognition for early detecting Alzheimer’s disease by using machine learning algorithms. In: International Conference on Engineering and MIS (ICEMIS), pp. 1-6 (2022)

4. Fraser, K.C., Meltzer, J.A., Rudzicz, F.: Linguistic features identify alzheimer’s disease in narrative speech. J. Alzheimer’s Dis. 49(2), 407–422 (2015)

5. UCI Machine Learning Repository. Parkinson’s Disease Classification Dataset. https://archive.ics.uci.edu/ml/datasets/Parkinson%27s+Disease+Classification https://drive.google.com/drive/folders/1E-Bde8y_7nqU30TqHNSW17r5EY1CP8P9

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