An Application-Based Review of Recent Advances of Data Mining in Healthcare

Background: Data mining as an integral part of the knowledge discovery in database (KDD) has gained significant attention over the past few years. By and large, data mining is the process of finding interesting structures in a considerably voluminous amount of data. Owing to its methods and algorithms supporting variable types of data, the data mining approach has been applied in many scientific areas, including the healthcare industry. Regarding this matter, in this paper, we elaborate on the latest papers, including data miningtechniques and algorithms in the healthcare field of research. Results: We present a data mining review based on the newest researches. Afterward, we categorize data mining papers in healthcare based on supervised and unsupervised learning paradigms as well as classifying them in terms of their applications in the healthcare domain. Conclusions: In every healthcare application, we propose some summary points of the papers. At last, we delve into the absence and hence, the necessity of existing some novel methods in healthcare domains in this researches.

Abstract licence: CC BY-NC

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