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Journals / Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi / 2019 / Cilt: 11 - Sayı: 1

Classifying White Blood Cells Using Machine Learning Algorithms

Abdullah ELEN
M. Kamil TURAN
Pages
141–152
Publication Date
2019-01-31
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results, the Multinomial Logistic Regression (MLR) algorithm performed better than the other methods with an average 95% test success.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Blood and its components have an important place in human life and are the best indicator tool in determining many pathological conditions.
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Key Findings & Data:In this study, 350 microscopic blood smear images were tested with 6 different machine learning algorithms for the classification of white blood cells and their performances were compared. 35 different geometric and statistical (texture) features have been extracted from blood images for training and test parameters of machine learning algorithms.
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Conclusion & Impact:According to the results, the Multinomial Logistic Regression (MLR) algorithm performed better than the other methods with an average 95% test success.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:WBC classification · leukocytes · blood cells

Abstract

Blood and its components have an important place in human life and are the best indicator tool in determining many pathological conditions. In particular, the classification of white blood cells is of great importance for the diagnosis of hematological diseases. In this study, 350 microscopic blood smear images were tested with 6 different machine learning algorithms for the classification of white blood cells and their performances were compared. 35 different geometric and statistical (texture) features have been extracted from blood images for training and test parameters of machine learning algorithms. According to the results, the Multinomial Logistic Regression (MLR) algorithm performed better than the other methods with an average 95% test success. The MLR can be used for automatic classification of white blood cells. It can be used especially as a source for diagnosis of diseases for hematologists and internal medicine specialists.

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Cite This Article

ELEN, A., TURAN, M. K. (2019). Classifying White Blood Cells Using Machine Learning Algorithms. Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi, Cilt: 11 - Sayı: 1, 141–152. https://ajindex.com/articles/889391

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