Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART
Rule induction has played an important role in implementing a medical expert system in the past decade, especially the Thalassemia Expert System. Due to the fact that Thalassemia indicators used in diagnosising types of Thalassemia are very complex, the induction rules C5.0 and Classification and Re...
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th-cmuir.6653943832-39332014-08-30T02:35:29Z Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART Paokanta P. Ceccarelli M. Harnpornchai N. Chakpitak N. Srichairatanakool S. Rule induction has played an important role in implementing a medical expert system in the past decade, especially the Thalassemia Expert System. Due to the fact that Thalassemia indicators used in diagnosising types of Thalassemia are very complex, the induction rules C5.0 and Classification and Regression Tree (CART) will be used to elicit new information about Thalassemia. The results obtained from using both algorithms show the different rules separating types of this disease. In the future, these results will be used to develop the Thalassemia Expert System and these results will be compared to find a suitable algorithm. Other algorithms will also be considered. © 2012 ICIC International. 2014-08-30T02:35:29Z 2014-08-30T02:35:29Z 2012 Article 1881803X http://www.scopus.com/inward/record.url?eid=2-s2.0-84856953354&partnerID=40&md5=aa4ad6162b43cbc714eb17afdbbcf61b http://cmuir.cmu.ac.th/handle/6653943832/3933 English |
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Rule induction has played an important role in implementing a medical expert system in the past decade, especially the Thalassemia Expert System. Due to the fact that Thalassemia indicators used in diagnosising types of Thalassemia are very complex, the induction rules C5.0 and Classification and Regression Tree (CART) will be used to elicit new information about Thalassemia. The results obtained from using both algorithms show the different rules separating types of this disease. In the future, these results will be used to develop the Thalassemia Expert System and these results will be compared to find a suitable algorithm. Other algorithms will also be considered. © 2012 ICIC International. |
| format |
Article |
| author |
Paokanta P. Ceccarelli M. Harnpornchai N. Chakpitak N. Srichairatanakool S. |
| spellingShingle |
Paokanta P. Ceccarelli M. Harnpornchai N. Chakpitak N. Srichairatanakool S. Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| author_facet |
Paokanta P. Ceccarelli M. Harnpornchai N. Chakpitak N. Srichairatanakool S. |
| author_sort |
Paokanta P. |
| title |
Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| title_short |
Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| title_full |
Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| title_fullStr |
Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| title_full_unstemmed |
Rule induction for screening Thalassemia using machine learning techniques: C5.0 and CART |
| title_sort |
rule induction for screening thalassemia using machine learning techniques: c5.0 and cart |
| publishDate |
2014 |
| url |
http://www.scopus.com/inward/record.url?eid=2-s2.0-84856953354&partnerID=40&md5=aa4ad6162b43cbc714eb17afdbbcf61b http://cmuir.cmu.ac.th/handle/6653943832/3933 |
| _version_ |
1681420142101135360 |