Parkinson’s Disease Classification Employing a Questionnaire of Non-motor Symptoms and Machine Learning Methods

• Rafael Alves Padilha UFG
• Juliana Paula Felix UFG
• Rogerio Salvini UFG

DOI: https://doi.org/10.5753/erigo.2024.5091

Resumo

This work presents a machine learning approach to aid in the classification of Parkinson’s disease (PD). Answers to a 30-question non-motor symptoms questionnaire are used as input for two classifiers that focus on differentiating Parkinson’s subjects (PD) from healthy subjects and PD vs. patients with differential diagnoses. The method was evaluated using a cross-validation technique, and the results surpass those in the literature.

Palavras-chave: Parkinson’s disease, machine learning, non-motor symptoms, questionnaire, classification

Referências

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Varghese, J., Brenner, A., Plagwitz, L., van Alen, C., Fujarski, M., and Warnecke, T. (2024b). PADS-Parkinsons Disease Smartwatch dataset. [link].