Figure 5.

An illustration of the supervised ML algorithms used in comparative motor pre-clinical assessments for the classification of PD.

After motor data is acquired from all groups, the algorithm extracts notable distinguishing features, distributing the subjects into three different datasets. The reference dataset (2C₆₀, 2C₉₀, 3C₉₀; Rovini et al., 2018). The dimensionality of the dataset is reduced before being fed into the supervised learning algorithm itself, where training takes place, then model testing. The algorithm output comes in the form of a confusion matrix, which is transformed into an evaluation matrix capable of categorizing disease types based on their distinguishing features. Created with BioRender.com.