Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis

Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis

BackgroundLeukemia is the 11th most prevalent type of cancer worldwide, with acute myeloid leukemia (AML) being the most frequent malignant blood malignancy in adults. Microscopic blood tests are the most common methods for identifying leukemia subtypes. An automated optical image-processing system...

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Bibliographic Details
Main Authors: Feras Al-Obeidat, Wael Hafez, Asrar Rashid, Mahir Khalil Jallo, Munier Gador, Ivan Cherrez-Ojeda, Daniel Simancas-Racines
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Big Data
Subjects:
artificial intelligence
acute myeloid leukemia
blood images
machine learning
neural networks
meta-analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2024.1402926/full
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https://www.frontiersin.org/articles/10.3389/fdata.2024.1402926/full

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