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Classification of blasts in acute leukemia blood samples using k-nearest neighbour

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Main Authors: Nadiatun Zawiyah, Supardi, Mohd Yusoff, Mashor, Prof. Madya Dr., Nor Hazlyna, Harun, Fatimatul Anis, Bakri, Rosline, Hassan, Dr.
Other Authors: nadiatun@gmail.com
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2013
Subjects:
Acute leukemia
Classification
K-nearest neighbour
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26524
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spelling my.unimap-265242014-06-27T09:47:34Z Classification of blasts in acute leukemia blood samples using k-nearest neighbour Nadiatun Zawiyah, Supardi Mohd Yusoff, Mashor, Prof. Madya Dr. Nor Hazlyna, Harun Fatimatul Anis, Bakri Rosline, Hassan, Dr. nadiatun@gmail.com yusoff@unimap.edu.my hazlyna_harun@yahoo.com fatimatulanis@yahoo.com.my roslinehassan@gmail.com Acute leukemia Classification K-nearest neighbour Link to publisher's homepage at http://ieeexplore.ieee.org/ The k-nearest neighbor (k-NN) is a traditional method and one of the simplest methods for classification problems. Even so, results obtained through k-NN had been promising in many different fields. Therefore, this paper presents the study on blasts classifying in acute leukemia into two major forms which are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL) by using k-NN. 12 main features that represent size, color-based and shape were extracted from acute leukemia blood images. The k values and distance metric of k-NN were tested in order to find suitable parameters to be applied in the method of classifying the blasts. Results show that by having k 4 and applying cosine distance metric, the accuracy obtained could reach up to 80%. Thus, k-NN is applicable in the classification problem. 2013-07-09T04:11:59Z 2013-07-09T04:11:59Z 2012-03-23 Working Paper p. 461-465 978-146730961-5 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6194769 http://hdl.handle.net/123456789/26524 en Proceedings of the International Colloquium on Signal Processing and Its Applications (CSPA 2012) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Acute leukemia
Classification
K-nearest neighbour
spellingShingle Acute leukemia
Classification
K-nearest neighbour
Nadiatun Zawiyah, Supardi
Mohd Yusoff, Mashor, Prof. Madya Dr.
Nor Hazlyna, Harun
Fatimatul Anis, Bakri
Rosline, Hassan, Dr.
Classification of blasts in acute leukemia blood samples using k-nearest neighbour
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 nadiatun@gmail.com
author_facet nadiatun@gmail.com
Nadiatun Zawiyah, Supardi
Mohd Yusoff, Mashor, Prof. Madya Dr.
Nor Hazlyna, Harun
Fatimatul Anis, Bakri
Rosline, Hassan, Dr.
format Working Paper
author Nadiatun Zawiyah, Supardi
Mohd Yusoff, Mashor, Prof. Madya Dr.
Nor Hazlyna, Harun
Fatimatul Anis, Bakri
Rosline, Hassan, Dr.
author_sort Nadiatun Zawiyah, Supardi
title Classification of blasts in acute leukemia blood samples using k-nearest neighbour
title_short Classification of blasts in acute leukemia blood samples using k-nearest neighbour
title_full Classification of blasts in acute leukemia blood samples using k-nearest neighbour
title_fullStr Classification of blasts in acute leukemia blood samples using k-nearest neighbour
title_full_unstemmed Classification of blasts in acute leukemia blood samples using k-nearest neighbour
title_sort classification of blasts in acute leukemia blood samples using k-nearest neighbour
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/26524
_version_ 1643794973206773760
score 13.214268

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