Leukemia Classification using a Convolutional Neural Network of AML Images

Autor:	Karrar A. Kadhim, Fallah H Najjar, Ali Abdulhussein Waad, Ibrahim H Al-Kharsan, Zaid Nidhal Khudhair, Ali Aqeel Salim
Rok vydání:	2023
Předmět:	General Mathematics General Physics and Astronomy General Chemistry General Agricultural and Biological Sciences General Biochemistry Genetics and Molecular Biology
Zdroj:	Malaysian Journal of Fundamental and Applied Sciences. 19:306-312
ISSN:	2289-599X 2289-5981
DOI:	10.11113/mjfas.v19n3.2901
Popis:	Among the most pressing issues in the field of illness diagnostics is identifying and diagnosing leukemia at its earliest stages, which requires accurate distinction of malignant leukocytes at a low cost. Leukemia is quite common, yet laboratory diagnostic centres often lack the necessary technology to diagnose the disease properly, and the available procedures take a long time. They are considering the efficacy of machine learning (ML) in illness diagnostics and that deep learning as a machine learning method is becoming critical. This study proposes a convolutional neural network (CNN) deep learning model for leukemia diagnosis utilizing the AML (acute myeloid leukemia) dataset. The classification using the proposed method achieved results that exceeded 98% accuracy, the sensitivity of 94.73% and specificity of 98.87%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::722f06e5bf07a4d3ad97115f9b5e0105 https://doi.org/10.11113/mjfas.v19n3.2901 Zobrazit plný text záznamu