期刊名称：International Journal of Data and Network Science
印刷版ISSN：2561-8148
电子版ISSN：2561-8156
出版年度：2019
卷号：3
期号：2
页码：47-70
DOI：10.5267/j.ijdns.2019.1.003
出版社：Growing Science
摘要：Due to the increasing technological advances in all fields, a considerable amount of data has been collected to be processed for different purposes. Data mining is the process of determining and an-alyzing hidden information from different perspectives to obtain useful knowledge. Data mining can have many various applications, one of them is in medical diagnosis. Today, many diseases are regarded as dangerous and deadly. Heart disease, breast cancer, and diabetes are among the most dangerous ones. This paper investigates 168 articles associated with the implementation of data mining for diagnosing such diseases. The study concentrates on 85 selected papers which have received more attention between 1997 and 2018. All algorithms, data mining models, and evaluation methods are thoroughly reviewed with special consideration. The study attempts to determine the most efficient data mining methods used for medical diagnosing purposes. Also, one of the other significant results of this study is the detection of research gaps in the application of data mining in health care.
关键词：Healthcare; Classification; Heart Disease; Breast Cancer;Diabetes Mellitus; Review
