Download This PaperReview on Trait Selection of Tumor in the Field of Oncology With the Aid of Data Mining
9 Pages Posted: 15 Apr 2020
Date Written: April 13, 2020
Abstract
Feature selection is the important technique which plays a pivotal role in the process of data mining. This is mainly needed to deal with the extreme number of features, normally which can turn into a computational over burden on the process of learning algorithms. Such type of algorithm is also necessary, even when the computational resources are not panic, since it improves the accuracy of the machine learning tasks. In the field of medical science there are various kinds of problem in the area of medical imaging as like extraction, classification, segmentation, selection and etc. On the other side Medical datasets are normally categorized by gigantic extent of disease measurements and comparatively little quantity of patient records. Such feature selection are not appropriate, where all such immaterial and redundancy features are extremely typical to evaluate. On the contrary, the huge number of features may cause the problem of memory storage in order to represent the data set. In such a situation various kinds of data mining algorithms or techniques can be implemented for dealing with such a huge amount of data with precision. This paper basically represents a brief review about the medical image feature selection for the diagnosis of the tumor by the help of data mining techniques.
Keywords: Data mining, Medical dataset, Cancer diagnosis, Tumor Analyzing
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