This review was conducted between December 2018 and March 2019 at Isfahan University of Medical Sciences. A review of various studies revealed what data mining techniques to predict the probability of survival, what risk factors for these predictions, what criteria for evaluating data mining techniques, and finally what data sources for it have been used to predict the surv...

Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applicat...

ata Mining is a discovery of knowledge used basically used for finding or exploring the new facts among datasets. It allows the user to find the hidden data among available datasets. Data mining consists of various components including clustering, classification, association rules, sequence analysis etc. Unlabeled data are becoming common and mining such databases becomes more challenging. Clus...

Clustering is an extensively studied data mining problem in the text domains. The difficulty finds numerous applications in customer segmentation, classification, collaborative filtering, visualization, document organization, and indexing. In text mining, clustering the sentence is one of the processes and used within general text mining tasks. Several clustering methods and algorithms are used...

clinical databases can be categorized as big data, include large quantities of information about patients and their medical conditions. analyzing the quantitative and qualitative clinical data in addition with discovering relationships among huge number of samples using data mining techniques could unveil hidden medical knowledge in terms of correlation and association of apparently independent...

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...