Timely Diagnosis of Acute Lymphoblastic Leukemia Using Artificial Intelligence-Oriented Deep Learning Methods

Table 6

Comparison of proposed networks with other machine learning-based classifiers.

Classifier	Training accuracy
VGG-16	0.9741
ResNet-50	0.9576
Proposed CNN	0.8579
RF	0.8172
LR	0.7988
SVM	0.7928
KNN	0.7789
SGD	0.6891
MLP	0.2733