Parkinson’s disease is a neurological disorder that causes partial or complete loss of motor reflexes and speech and affects thinking, behavior, and other vital functions affecting the nervous system. Parkinson’s disease causes impaired speech and motor abilities (writing, balance, etc.) in about 90% of patients and is often seen in older people. Some signs (deterioration of vocal cords) in medical voice recordings from Parkinson’s patients are used to diagnose this disease. The database used in this study contains biomedical speech voice from 31 people of different age and sex related to this disease. The performance comparison of the machine learning algorithms k-Nearest Neighborhood (k-NN), Random Forest, Naive Bayes, and Support Vector Machine classifiers was performed with the used database. Moreover, the best classifier was determined for the diagnosis of Parkinson’s disease. Eleven different training and test data (45 × 55, 50 × 50, 55 × 45, 60 × 40, 65 × 35, 70 × 30, 75 × 25, 80 × 20, 85 × 15, 90 × 10, 95 × 5) were processed separately. The data obtained from these training and tests were compared with statistical measurements. The training results of the k-NN classification algorithm were generally 100% successful. The best test result was obtained from Random Forest classifier with 85.81%. All statistical results and measured values are given in detail in the experimental studies section.

Graphical abstract

帕金森病是一种神经系统疾病，会导致运动反射和言语部分或完全丧失，并影响思维、行为和其他影响神经系统的重要功能。大约 90% 的帕金森氏症患者会导致言语和运动能力（写作、平衡等）受损，并且常见于老年人。帕金森病患者的医疗录音中的一些迹象（声带退化）可用于诊断这种疾病。本研究中使用的数据库包含来自与该疾病相关的 31 名不同年龄和性别的人的生物医学语音。使用所使用的数据库对机器学习算法 k-最近邻域 (k-NN)、随机森林、朴素贝叶斯和支持向量机分类器的性能进行了比较。而且，确定了诊断帕金森病的最佳分类器。十一种不同的训练和测试数据（45×55、50×50、55×45、60×40、65×35、70×30、75×25、80×20、85×15、90×10、95×5 ) 分别处理。将从这些训练和测试中获得的数据与统计测量值进行比较。k-NN分类算法的训练结果一般都是100%成功。最好的测试结果是从随机森林分类器中获得的，为 85.81%。所有统计结果和测量值都在实验研究部分详细给出。将从这些训练和测试中获得的数据与统计测量值进行比较。k-NN分类算法的训练结果一般都是100%成功。最好的测试结果是从随机森林分类器中获得的，为 85.81%。所有统计结果和测量值都在实验研究部分详细给出。将从这些训练和测试中获得的数据与统计测量值进行比较。k-NN分类算法的训练结果一般都是100%成功。最好的测试结果是从随机森林分类器中获得的，为 85.81%。所有统计结果和测量值都在实验研究部分详细给出。

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