文章基本信息

标题：Mining Complete Blood Count Reports For Disease Discovery
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作者：Samiullah Jatoi ; M. Aamir Panhwar ; M. Sulleman Memon 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2018
卷号：18
期号：1
页码：121-127
出版社：International Journal of Computer Science and Network Security
摘要：Healthcare systems create a massive amount of data from medical tests. Data mining is the method to determine patterns in huge data sets such as medical examinations. Blood diseases are not the exception there are many test data that can be collected from their patients. In this research, we have applied data mining technique to discover the core-relationship between Anemia and Thalassemia from Complete Blood Count (CBC)test. The relationship can be exploited to identify and predict the possibility of getting Thalassemia in the patients suffering from Anemia. We have performed experiments using blood test data set collected from Diagnostic and Research Laboratory of LUMHS in Pakistan. Naive Bayesian Network algorithm is used to analyze and evaluate the data set. The Final results show that Bayesian Network has the best capability to predict core-relate between diseases with an accuracy of 98%.
关键词：;;;; ;;;;;; CBC; KNN; Thalassemia; Anemia and Bayesian Network