“…Many researchers have worked for the diagnosis of PD using machine learning (ML) techniques. Authors of [14,15] have used support vector machine (SVM), authors of [16][17][18][19] have used neural network (NN), authors of [20,21] have used fuzzy logic (FL), authors of [22] have used genetic programming (GP), authors of [23] have used random forest (RF), authors of [24] have used decision tree (DT), authors of [25] have used GP and expectation maximization (EM), authors of [26] have used KNN, FL, and K-means (KM), authors of [27] have used SVM and NN, authors of [28] have used SVM, KNN, FL, and Principal component analysis (PCA), authors of [29] have used NN, EM, PCA, and linear discriminant analysis (LDA), authors of [30] have used KNN, NN, and association rule (AR), authors of [31] have used SVM, KNN, and naïve Bayes (NB). Table 1 shows the various studies conducted on the automated diagnosis of PD.…”