Table 6.

Comparison with other ASD classification research based on MRI data of ABIDE dataset.

Ref	ASD group			TD group			sMRI features	Classification method	Classification accuracy	Note
	Age	Gender	Size	Age	Gender	Size
Haar et al. (2014)	6–35	Male only	453	6–35	Male only	453	Regional volume, surface area and cortical thickness	LDA, QDA	< 60%	Performed two analyses, based on strict/relaxed criteria.
Sabuncu et al. (2015)	17.8 ± 7.4	88.6% Male	325	17.9 ± 7.4	88.6% Male	325	Regional volume, surface area and cortical thickness	SVM, NAF, RVM	< 60%	None.
Katuwal et al. (2015)	Unknown	Male only	373	Unknown	Male only	361	Volume, surface area, cortical thickness, thickness std., mean curvature, Gaussian curvature, folding index	RF, GBM, SVM	60%	None.
Katuwal et al. (2016)	17.9 ± 8.7	Male only	361	18.1 ± 8.2	Male only	373	Curvature and folding index	GBM	60%	Adding VIQ and age to morphometric features.
Zheng et al. (2019)	Depends on site	Depends on site	66	Depends on site	Depends on site	66	Seven morphological features of each of the 360 brain regions, elastic network, multi-feature-based networks	SVM	78.63%	High-functioning adults with ASD.
This study	6–34	Male only	364	6–34	Male only	381	Patch-based features derived from hippocampus	Six ensemble classifiers	> 80%	None.

LDA = Linear Discriminant Classifier; QDA = Quadratic Discriminant Classifier; SVM = Support Vector Machine; NAF = Neighborhood Approximation Forest; RVM = Bayesian Relevance Vector Machine; RF = Random Forest; GBM = Gradient Boosting Machine.