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http://dx.doi.org/10.9717/kmms.2020.23.2.174

Acute Leukemia Classification Using Sequential Neural Network Classifier in Clinical Decision Support System  

Lim, Seon-Ja (Dept. of Computer Engineering, Pukyong National University)
Vincent, Ivan (Dept. of IT Convergence and Applications Eng., Pukyong National University)
Kwon, Ki-Ryong (Dept. of IT Convergence and Applications Eng., Pukyong National University)
Yun, Sung-Dae (Dept. of Computer Engineering, Pukyong National University)
Publication Information
Journal of Korea Multimedia Society / v.23, no.2, 2020 , pp. 174-185 More about this Journal
Abstract
Leukemia induced death has been listed in the top ten most dangerous mortality basis for human being. Some of the reason is due to slow decision-making process which caused suitable medical treatment cannot be applied on time. Therefore, good clinical decision support for acute leukemia type classification has become a necessity. In this paper, the author proposed a novel approach to perform acute leukemia type classification using sequential neural network classifier. Our experimental result only cover the first classification process which shows an excellent performance in differentiating normal and abnormal cells. Further development is needed to prove the effectiveness of second neural network classifier.
Keywords
Acute Leukemia Classification; Sequential Neural Network; Clinical Decision Support System; K-Means Clustering;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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