Disease diagnosis using machine learning techniques: A review and classification

• Main Authors: Nilashi, Mehrbakhsh, Ahmadi, Neda, Samad, Sarminah, Shahmoradi, Leila, Ahmadi, Hossein, Ibrahim, Othman, Asadi, Shahla, Abdullah, Rusli, Abumalloh, Rabab Ali, Yadegaridehkordi, Elaheh
• Format: Article
• Published: Penerbit UTM Press 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/87043/; https://jscdss.com/index.php/files/article/view/224

In this research, we reviewed and classified academic conference and journal papers;which used data mining techniques in disease classification and diagnosis based on public medical datasets published between 2007 and 2019. The results of this review demonstrated that the application of data miningtechniquesin disease classification hasexperienced a dramatic rise in recent years. The finding of this paper also revealed that there was minimal focus on developing methods using incremental version of data mining techniques. We hope that this research will provide useful information about various data mining techniques, their application in disease diagnosis,and help researchers in developing medical decision support systems with insightsinto the state-of-the-art of developmentmethods.