The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique
It is undeniable that laboratory information is important in healthcare in many ways such as management, planning, and quality improvement. Laboratory diagnosis and laboratory results from each patient are organized from every treatment. These data are useful for retrospective study exploring a rela...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Hematology |
| Online Access: | http://dx.doi.org/10.1155/2014/493706 |
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| author | Sarawut Saichanma Sucha Chulsomlee Nonthaya Thangrua Pornsuri Pongsuchart Duangmanee Sanmun |
| author_facet | Sarawut Saichanma Sucha Chulsomlee Nonthaya Thangrua Pornsuri Pongsuchart Duangmanee Sanmun |
| author_sort | Sarawut Saichanma |
| collection | DOAJ |
| description | It is undeniable that laboratory information is important in healthcare in many ways such as management, planning, and quality improvement. Laboratory diagnosis and laboratory results from each patient are organized from every treatment. These data are useful for retrospective study exploring a relationship between laboratory results and diseases. By doing so, it increases efficiency in diagnosis and quality in laboratory report. Our study will utilize J48 algorithm, a data mining technique to predict abnormality in peripheral blood smear from 1,362 students by using 13 data set of hematological parameters gathered from automated blood cell counter. We found that the decision tree which is created from the algorithm can be used as a practical guideline for RBC morphology prediction by using 4 hematological parameters (MCV, MCH, Hct, and RBC). The average prediction of RBC morphology has true positive, false positive, precision, recall, and accuracy of 0.940, 0.050, 0.945, 0.940, and 0.943, respectively. A newly found paradigm in managing medical laboratory information will be helpful in organizing, researching, and assisting correlation in multiple disciplinary other than medical science which will eventually lead to an improvement in quality of test results and more accurate diagnosis. |
| format | Article |
| id | doaj-art-d218fb538399459b8ebf181176a72f8a |
| institution | Kabale University |
| issn | 1687-9104 1687-9112 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Hematology |
| spelling | doaj-art-d218fb538399459b8ebf181176a72f8a2025-02-03T01:28:53ZengWileyAdvances in Hematology1687-91041687-91122014-01-01201410.1155/2014/493706493706The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining TechniqueSarawut Saichanma0Sucha Chulsomlee1Nonthaya Thangrua2Pornsuri Pongsuchart3Duangmanee Sanmun4Division of Clinical Microscopy, Faculty of Medical Technology, Huachiew Chalermprakiet University, Samut Prakan 10540, ThailandDivision of Clinical Microscopy, Faculty of Medical Technology, Huachiew Chalermprakiet University, Samut Prakan 10540, ThailandDivision of Clinical Microscopy, Faculty of Medical Technology, Huachiew Chalermprakiet University, Samut Prakan 10540, ThailandDivision of Clinical Microscopy, Faculty of Medical Technology, Huachiew Chalermprakiet University, Samut Prakan 10540, ThailandDivision of Clinical Microscopy, Faculty of Medical Technology, Huachiew Chalermprakiet University, Samut Prakan 10540, ThailandIt is undeniable that laboratory information is important in healthcare in many ways such as management, planning, and quality improvement. Laboratory diagnosis and laboratory results from each patient are organized from every treatment. These data are useful for retrospective study exploring a relationship between laboratory results and diseases. By doing so, it increases efficiency in diagnosis and quality in laboratory report. Our study will utilize J48 algorithm, a data mining technique to predict abnormality in peripheral blood smear from 1,362 students by using 13 data set of hematological parameters gathered from automated blood cell counter. We found that the decision tree which is created from the algorithm can be used as a practical guideline for RBC morphology prediction by using 4 hematological parameters (MCV, MCH, Hct, and RBC). The average prediction of RBC morphology has true positive, false positive, precision, recall, and accuracy of 0.940, 0.050, 0.945, 0.940, and 0.943, respectively. A newly found paradigm in managing medical laboratory information will be helpful in organizing, researching, and assisting correlation in multiple disciplinary other than medical science which will eventually lead to an improvement in quality of test results and more accurate diagnosis.http://dx.doi.org/10.1155/2014/493706 |
| spellingShingle | Sarawut Saichanma Sucha Chulsomlee Nonthaya Thangrua Pornsuri Pongsuchart Duangmanee Sanmun The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique Advances in Hematology |
| title | The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique |
| title_full | The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique |
| title_fullStr | The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique |
| title_full_unstemmed | The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique |
| title_short | The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique |
| title_sort | observation report of red blood cell morphology in thailand teenager by using data mining technique |
| url | http://dx.doi.org/10.1155/2014/493706 |
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