A novel voice classification based on Gower distance for Parkinson disease detection

Author:

Noaman Kadhim Mustafa,Al-Shammary Dhiah,Sufi Fahim

Funder

Monash University

Publisher

Elsevier BV

Reference27 articles.

1. Parkinson’s disease and its management: Part 1: disease entity, risk factors, pathophysiology, clinical presentation, and diagnosis;DeMaagd;Pharm. Ther.,2015

2. Prevalence of Parkinson’s disease in Europe: a collaborative study of population-based cohorts. Neurologic Diseases in the Elderly Research Group;De Rijk;Neurology,2000

3. Cantürk, ̇I.; Karabiber, F. A machine learning system for the diagnosis of Parkinson’s disease from speech signals and its application to multiple speech signal types. Arab. J. Sci. Eng. 2016, 41, 5049–5059.

4. Ricciardi, C. et al. (2020). Classifying Different Stages of Parkinson’s Disease Through Random Forests. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_140.

5. Efficient ECG classification based on chi-square distance for arrhythmia detection;Al-Shammary;J. Electron. Sci. Technol.,2024

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