Recognition and categorization of blood groups by machine learning and image processing method
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Дата
2024
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Igor Sikorsky Kyiv Polytechnic Institute
Анотація
Background. Red blood cells are one of the components of blood. Blood is an important fluid in the human
body. Knowing the blood groups is essential in blood transfusion operations, which depend on fixed conditions
to avoid fatal errors. The method that is used to determine the blood groups is a traditional method
that relies on medical laboratory technicians, as it is subject to human errors.
Objective. This paper aims to design and implement a prototype to detect and classify blood groups to avoid
human error in blood group detection. The proposed system employs image processing and machine learning
algorithms for blood group detection and classification.
Methods. The system consists of three stages. First, samples were collected from volunteers. Second, images of
the samples were captured using a camera. Third, the images were analyzed using two methods: image processing
via MATLAB and machine learning algorithms via Orange, for blood group detection and classification.
Results. The accuracy in processing images using the MATLAB program reached 100%, with processing
time ranged from 1.5 to 1.6 seconds. Additionally, using machine learning with neural networks in the
Orange program, the accuracy was 99.7%, with training times of 13.7 seconds and testing times of
1.2 seconds. Neural networks outperformed other models, as shown in the experimental results. The study
concluded that automated blood type detection using image processing and machine learning methods is effective
and feasible compared to manual methods. The proposed system outperformed previous studies in
terms of accuracy, processing time, training time, and testing time using both methods.
Conclusions. This study underscores the urgent need for precise blood type determination before emergency
blood transfusions, which currently relies on manual inspection and is susceptible to human errors. These errors
have the potential to endanger lives during blood transfusions. The main goal of the research was to develop
an approach that combines image processing and machine learning to accurately classify blood groups.
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Бібліографічний опис
Mustafa F. Mahmood. Recognition and categorization of blood groups by machine learning and image processing method / Mustafa F. Mahmood // Innovative Biosystems and Bioengineering : international scientific journal. – 2024. – Vol. 8, No. 2. – P. 53-68. – Bibliogr.: 50 ref.