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Predictive data mining approaches in medical diagnosis: A review of some diseases prediction

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. | Predictive data mining approaches in medical diagnosis A review of some diseases prediction International Journal of Data and Network Science 3 2019 47 70 Contents lists available at GrowingScience International Journal of Data and Network Science homepage www.GrowingScience.com ijds Predictive data mining approaches in medical diagnosis A review of some diseases prediction Ramin Ghorbania and Rouzbeh Ghousia a Department of Industrial Engineering Iran University of Science and Technology Tehran Iran CHRONICLE ABSTRACT Article history Due to the increasing technological advances in all fields a considerable amount of data has been Received October 18 2018 collected to be processed for different purposes. Data mining is the process of determining and Received in revised format De- analyzing hidden information from different perspectives to obtain useful knowledge. Data min- cember 20 2018 ing can have many various applications one of them is in medical diagnosis. Today many dis- Accepted January 8 2019 Available online eases are regarded as dangerous and deadly. Heart disease breast cancer and diabetes are among January 8 2019 the most dangerous ones. This paper investigates 168 articles associated with the implementation Keywords of data mining for diagnosing such diseases. The study concentrates on 85 selected papers which Healthcare have received more attention between 1997 and 2018. All algorithms data mining models and Classification evaluation methods are thoroughly reviewed with special consideration. The study attempts to Heart Disease determine the most efficient data mining methods used for medical diagnosing purposes. Also Breast Cancer one of the other significant results of this study is the detection of research gaps in the application Diabetes Mellitus of data mining in health care. Review 2019 by the authors licensee Growing Science Canada. 1. Introduction We live in a world where large volumes of data are collected every day and analyzing such .