Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr
The myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by dysregulated proliferation and expansion of one or more of the myeloid lineages. The initial symptoms of MPN is a bone marrow abnormalities when producing red blood cells, white blood cells and plat...
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| Format: | Article |
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Universitas Negeri Semarang
2020-06-01
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| Series: | Scientific Journal of Informatics |
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| Online Access: | https://journal.unnes.ac.id/nju/index.php/sji/article/view/24372 |
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| author | Zilvanhisna Emka Fitri Lindri Nalentine Yolanda Syahputri Arizal Mujibtamala Nanda Imron |
| author_facet | Zilvanhisna Emka Fitri Lindri Nalentine Yolanda Syahputri Arizal Mujibtamala Nanda Imron |
| author_sort | Zilvanhisna Emka Fitri |
| collection | DOAJ |
| description | The myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by dysregulated proliferation and expansion of one or more of the myeloid lineages. The initial symptoms of MPN is a bone marrow abnormalities when producing red blood cells, white blood cells and platelets in large numbers and uncontrolled. An automatic and accurate white blood cell abnormality classification system is needed. This research uses digital image processing techniques such as conversion to the modified CIELab color space, segmentation techniques based on threshold values and feature extraction processes that produce four morphological features consisting of area, perimeter, metric and compactness. then the four features become input to the K-Nearest Neighborr (KNN) method. The testing process is based on variations in the value of K to get the best accuracy percentage of 94.3% tested on 159 test data. |
| format | Article |
| id | doaj-art-ba622bbd4dcf4138b672ad605eca9252 |
| institution | DOAJ |
| issn | 2407-7658 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | Universitas Negeri Semarang |
| record_format | Article |
| series | Scientific Journal of Informatics |
| spelling | doaj-art-ba622bbd4dcf4138b672ad605eca92522025-08-20T03:04:49ZengUniversitas Negeri SemarangScientific Journal of Informatics2407-76582020-06-017113614210.15294/sji.v7i1.243729860Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest NeighborrZilvanhisna Emka Fitri0Lindri Nalentine Yolanda Syahputri1Arizal Mujibtamala Nanda Imron2Politeknik Negeri JemberPoliteknik Negeri JemberUniversitas JemberThe myeloproliferative neoplasms (MPNs) are clonal hematopoietic stem cell disorders characterized by dysregulated proliferation and expansion of one or more of the myeloid lineages. The initial symptoms of MPN is a bone marrow abnormalities when producing red blood cells, white blood cells and platelets in large numbers and uncontrolled. An automatic and accurate white blood cell abnormality classification system is needed. This research uses digital image processing techniques such as conversion to the modified CIELab color space, segmentation techniques based on threshold values and feature extraction processes that produce four morphological features consisting of area, perimeter, metric and compactness. then the four features become input to the K-Nearest Neighborr (KNN) method. The testing process is based on variations in the value of K to get the best accuracy percentage of 94.3% tested on 159 test data.https://journal.unnes.ac.id/nju/index.php/sji/article/view/24372mpnswbc abnormalitiescielabthresholdingknn |
| spellingShingle | Zilvanhisna Emka Fitri Lindri Nalentine Yolanda Syahputri Arizal Mujibtamala Nanda Imron Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr Scientific Journal of Informatics mpns wbc abnormalities cielab thresholding knn |
| title | Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr |
| title_full | Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr |
| title_fullStr | Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr |
| title_full_unstemmed | Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr |
| title_short | Classification of White Blood Cell Abnormalities for Early Detection of Myeloproliferative Neoplasms Syndrome Based on K-Nearest Neighborr |
| title_sort | classification of white blood cell abnormalities for early detection of myeloproliferative neoplasms syndrome based on k nearest neighborr |
| topic | mpns wbc abnormalities cielab thresholding knn |
| url | https://journal.unnes.ac.id/nju/index.php/sji/article/view/24372 |
| work_keys_str_mv | AT zilvanhisnaemkafitri classificationofwhitebloodcellabnormalitiesforearlydetectionofmyeloproliferativeneoplasmssyndromebasedonknearestneighborr AT lindrinalentineyolandasyahputri classificationofwhitebloodcellabnormalitiesforearlydetectionofmyeloproliferativeneoplasmssyndromebasedonknearestneighborr AT arizalmujibtamalanandaimron classificationofwhitebloodcellabnormalitiesforearlydetectionofmyeloproliferativeneoplasmssyndromebasedonknearestneighborr |