A REVIEW OF DATA MINING TECHNIQUES IN MEDICINE

Ionela-Cătălina Zamfir and Ana-Maria Mihaela Iordache
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Ionela-Cătălina Zamfir: The Bucharest University of Economic Studies, Bucharest, Romania
Ana-Maria Mihaela Iordache: Romanian-American University, Bucharest, Romania

Journal of Information Systems & Operations Management, 2020, vol. 14, issue 1, 93-106

Abstract: Data mining techniques found applications in many areas since their development. New techniques or combination of techniques are created continuously. Techniques like supervised or unsupervised learning are used for prediction different diseases and have the aim to identify (diagnosis) the disease and predict the incidence or make predictions about treatment and survival rate. This paper presents the new trends in applying data mining in healthcare area, taking into account the most relevant papers in this respect. By analyzing both applied and review articles, using text mining on keywords and abstracts, it is revealing the most used methodologies (Support Vector Machines, Artificial Neural Networks, K-Means Algorithm, Decision Trees, Logistic Regression) as well as the areas of interest (prediction of different diseases, like: breast cancer, lung cancer, heart diseases, diabetes, thyroid or kidney diseases).

Date: 2020
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