Journal of Soft Computing Exploration
Vol. 5 No. 2 (2024): June 2024

Improved convolutional neural network model for leukemia classification using EfficientNetV2M and bayesian optimization

Wibowo, Kevyn Alifian Hernanda (Unknown)
Rianto, Nur Azis Kurnia (Unknown)
Unjung, Jumanto (Unknown)



Article Info

Publish Date
27 Jun 2024

Abstract

Leukemia is a health condition in which the body produces too many abnormal white blood cells or leukocytes. Leukemia can affect both children and adults. Early diagnosis of leukemia faces significant challenges, as diagnostic methods are time consuming, require experienced medical experts, and are expensive. Previous studies have been conducted using deep learning approaches, but it is still rare to find a model that shows the best performance and uses optimization methods to classify leukemia diseases. Therefore, a Convolutional Neural Network (CNN) model with EfficientNetV2M architecture and Bayesian Optimization is proposed as the main method assisted by ImageDataGenerator in preprocessing. This study shows a significant impact of Bayesian optimization with good Accuracy, Precision, Recall and F1-Score results of 91.37%, 93.00%, 87.00%, 89.00%, respectively, which are expected to improve the performance of the model in previous studies in classifying leukemia diseases.

Copyrights © 2024






Journal Info

Abbrev

joscex

Publisher

Subject

Computer Science & IT

Description

Journal of Soft Computing Exploration is a journal that publishes manuscripts of scientific research papers related to soft computing. The scope of research can be from the theory and scientific applications as well as the novelty of related knowledge insights. Soft Computing: Artificial ...