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Published online 2024 Mar 5. doi: 10.1186/s13040-024-00360-6

Table 3

Comparison with state-of-the-art methods on LGG and KIPAN datasets

MethodLGG (2 Categories)KIPAN (3 Categories)
ACC(%)F1(%)AUC(%)ACC(%)F1_w(%)F1_m(%)
(95% CI)(95% CI)(95% CI)(95% CI)(95% CI)(95% CI)
KNN72.9 (68.7-77.1)73.8 (69.7-77.9)79.9 (75.2-84.6)96.7 (95.3-98.1)96.7 (95.3-98.1)96.0 (94.3-97.7)
SVM75.4 (69.7-81.1)75.7 (69.5-81.9)75.4 (69.7-81.1)99.5 (99.1-99.9)99.5 (99.1-99.9)99.4 (98.9-99.9)
Lasso76.1 (73.9-78.3)76.7 (74.0-79.4)82.3 (78.9-85.7)97.4 (97.2-97.6)97.4 (97.2-97.6)97.2 (96.7-97.7)
RF74.8 (73.3-76.3)74.2 (73.0-75.4)82.3 (81.1-83.5)98.1 (97.4-98.8)98.1 (97.4-98.8)97.5 (96.1-98.9)
XGBoost75.6 (70.6-80.6)76.7 (72.7-80.7)84.0 (81.1-86.9)99.3 (98.3-100)99.3 (98.3-100)98.9 (97.2-100)
NN73.7 (70.8-76.6)74.8 (71.8-77.8)81.0 (76.4-85.6)99.1 (98.5-99.7)99.1 (98.5-99.7)99.1 (98.5-99.7)
GRridge74.6 (69.9-79.3)75.6 (71.1-80.1)82.6 (77.1-88.1)99.4 (98.9-99.9)99.4 (98.9-99.9)99.3 (98.8-99.8)
BPLSDA75.9 (72.8-79.0)73.8 (70.0-77.6)82.5 (79.6-85.4)93.3 (91.7-94.9)93.3 (91.7-94.9)91.9 (89.3-94.5)
BSPLSDA68.5 (65.1-71.9)66.2 (62.5-69.9)73.0 (69.8-76.2)91.9 (90.4-93.4)91.8 (90.2-93.4)89.5 (87.8-91.2)
CF81.1 (79.6-82.6)82.2 (81.7-82.7)88.1 (87.6-88.6)99.9 (99.7-100)99.9 (99.7-100)99.9 (99.7-100)
GMU80.3 (78.4-82.2)80.8 (79.3-82.3)88.6 (87.1-90.1)99.2 (98.6-99.8)99.2 (98.6-99.8)98.8 (97.7-99.9)
Mogonet81.6 (79.6-83.6)81.4 (79.7-83.1)84.0 (80.6-87.4)97.7 (95.7-99.7)97.6 (95.5-99.7)95.8 (91.8-99.8)
Dynamics83.3 (82.8-83.8)83.7 (83.5-83.9)88.5 (88.3-88.7)99.9 (99.8-100)99.9 (99.8-100)99.9 (99.8-100)
MOCAT(Ours)85.1 (84.4-85.8) 85.1 (84.1-86.1) 88.5 (88.0-89.0)99.9 (99.8-100)99.9 (99.8-100)99.8 (99.3-100)

Means and 95% confidence intervals (95% CIs) are presented, and the best results are in bold.The 95% CI is calculated using the t-distribution, with degrees of freedom set at n-1, where n is the number of experiments conducted.

Compared to the suboptimal model, the superior model is denoted by to indicate a statistically significant improvement (P<0.05) when using the two-sample t-test

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