Machine Learning Algorithms for Peripheral Blood Cell Classification - A Hemovision Project Experience
Mariana Dourado X. S. Santos, William Laus Bertemes, Iaan Mesquita de Souza, Mateus Henrique B. Andrades, Vinícius Sebba Patto · Revista de Informática Teórica e Aplicada · 2023
This research explores the use of machine learning algorithms to classify nucleated peripheral blood cells. The ResNet18 convolutional neural network was used to pre-process the images and replace the dense layers; and for the output, the Support Vector Machine (SVM) classifier was chosen. Images from different datasets were used for training and testing the model. Thus, the developed model achieved an accuracy and F1-Score of 99.96%. In face of the obtained results, it was found that machine learning algorithms can be satisfactorily integrated into educational and diagnostic support processes.