Detection of microcytic hypochromia using cbc and blood film features extracted from convolution neural network by different classifiers

Results achieved from the proposed method reflect that fused data set can effectively improve the identification ratio with a very limited number of patients diagnostic images and clinical data and feed-forward back-propagation neural network on this data set achieved accuracy, sensitivity, and specificity of 99, 1, and 0.98, respectively.