. Author manuscript; available in PMC: 2022 May 11.

Published in final edited form as: IEEE J Biomed Health Inform. 2021 May 11;25(5):1824–1831. doi: 10.1109/JBHI.2020.3025049

TABLE II.

Machine learning model performance for various feature sets

Feature Set	Model	ACC	SPE	SEN	AUC	F1
Spatiotemporal	SVM	*0.73*	*0.89*	0.55	0.73	*0.67*
Stride	LR	0.65	0.73	0.56	0.69	0.59
Aggregated Stride	LR	0.66	0.78	0.53	0.76	0.60
EDSS	SVM	0.62	*0.89*	0.33	0.71	0.46
PRM	SVM	0.70	0.84	0.56	0.74	0.65
PRM + EDSS	LR	0.70	0.79	*0.61*	*0.79*	*0.67*

SVM: Support Vector Machine; LR: Logistic Regression; AUC: Area Under the Receiver Operating Characteristic Curve; ACC: Accuracy; SPE: Specificity; SEN: Sensitivity; F1: F1-Score.