Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography

Table 4 Results of classification between MCI and AD

	Accuracy	Precision	Recall	F1 Score	AUC
LR
Clinical data	0.88 ± 0.00	0.84 ± 0.00	0.90 ± 0.00	0.88 ± 0.00	0.94 ± 0.00
Tau PET	0.84 ± 0.00	0.82 ± 0.00	0.82 ± 0.00	0.82 ± 0.00	0.90 ± 0.01
Clinical data with Tau	0.89 ± 0.02	0.88 ± 0.04	0.88 ± 0.05	0.86 ± 0.02	0.95 ± 0.01
SVM
Clinical	0.96 ± 0.00	0.92 ± 0.00	1.00 ± 0.00	0.96 ± 0.00	0.94 ± 0.00
Tau	0.88 ± 0.00	0.90 ± 0.00	0.83 ± 0.00	0.85 ± 0.00	0.89 ± 0.00
Clinical with Tau	0.96 ± 0.00	0.93 ± 0.04	0.98 ± 0.04	0.96 ± 0.00	0.95 ± 0.01
XGB
Clinical	0.88 ± 0.00	0.90 ± 0.00	0.83 ± 0.00	0.85 ± 0.00	0.95 ± 0.01
Tau	0.79 ± 0.02	0.86 ± 0.01	0.66 ± 0.04	0.71 ± 0.03	0.90 ± 0.00
Clinical with Tau	0.89 ± 0.04	0.89 ± 0.01	0.85 ± 0.10	0.84 ± 0.06	0.97 ± 0.01
MLP
Clinical	0.83 ± 0.10	0.84 ± 0.10	0.78 ± 0.16	0.78 ± 0.13	0.95 ± 0.11
Tau	0.82 ± 0.05	0.92 ± 0.07	0.70 ± 0.09	0.75 ± 0.07	0.90 ± 0.05
Clinical with Tau	0.86 ± 0.05	0.90 ± 0.05	0.82 ± 0.11	0.83 ± 0.07	0.97 ± 0.06

MCI mild cognitive impairment, AD Alzheimer’s disease, LR logistic regression, SVM support vector machine, XGB extreme gradient boosting, MLP multilayer perceptron, AUC area under the receiver operating characteristic curve .Values are presented as mean ± SD

ISSN: 1475-925X