TITLE

Predicting the Severity of Breast Masses with Data Mining Methods

AUTHOR(S)
Mokhtar, Sahar A.; Elsayad, Alaa. M.
PUB. DATE
March 2013
SOURCE
International Journal of Computer Science Issues (IJCSI);Mar2013, Vol. 10 Issue 2, p160
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Mammography is the most effective and available tool for breast cancer screening. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. Data mining algorithms could be used to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or to perform a short term follow-up examination instead. In this research paper data mining classification algorithms; Decision Tree (DT), Artificial Neural Network (ANN), and Support Vector Machine (SVM) are analyzed on mammographic masses dataset. The purpose of this study is to increase the ability of physicians to determine the severity (benign or malignant) of a mammographic mass lesion from BI-RADS attributes and the patient's age. The whole dataset is divided for training the models and test them by the ratio of 70:30% respectively and the performances of classification algorithms are compared through three statistical measures; sensitivity, specificity, and classification accuracy. Accuracy of DT, ANN and SVM are 78.12%, 80.56% and 81.25% of test samples respectively. Our analysis shows that out of these three classification models SVM predicts severity of breast cancer with least error rate and highest accuracy.
ACCESSION #
88874077

 

Related Articles

  • Statistical Measures to Determine Optimal Structure of Decision Tree: One versus One Support Vector Machine. Bala, Manju; Agrawal, R. K. // Defence Science Journal;2010, Vol. 60 Issue 4, p399 

    In this paper, one versus one optimal decision tree support vector machine (OvO-ODT SVM) framework is proposed to solve multi-class problems where the optimal structure of decision tree is determined using statistical measures, i.e., information gain, gini index, and chi-square. The performance...

  • A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification. MILI, Faissal; HAMDI, Manel // International Journal of Advanced Computer Science & Application;Aug2012, Vol. 3 Issue 8, p89 

    This paper presents a specific structure of neural network as the functional link artificial neural network (FLANN). This technique has been employed for classification tasks of data mining. In fact, there are a few studies that used this tool for solving classification problems. In this present...

  • Data Mining Techniques in Customer Churn Prediction. Tsai, Chih-Fong; Lu, Yu-Hsin // Recent Patents on Computer Science;2010, Vol. 3 Issue 1, p28 

    Customer churn prediction is one of the most important problems in customer relationship management (CRM). Its aim is to retain valuable customers to maximize the profit of a company. To predict whether a customer will be a churner or non-churner, there are a number of data mining techniques...

  • Predicting Students' Performance using Modified ID3 Algorithm. L., Ramanathan; Dhanda, Saksham; D., Suresh Kumar // International Journal of Engineering & Technology (0975-4024);Jun/Jul2013, Vol. 5 Issue 3, p2491 

    The ability to predict performance of students is very crucial in our present education system. We can use data mining concepts for this purpose. ID3 algorithm is one of the famous algorithms present today to generate decision trees. But this algorithm has a shortcoming that it is inclined to...

  • Experimental Analysis Towards Realizing Breast Cancer Prognosis Using Diverse Machine Learning Classifiers. Chaurasia, Sandeep; Chakrabarti, Prasun; Yu Cheng // Australian Journal of Basic & Applied Sciences;Jun2014, Vol. 8 Issue 9, p31 

    The adequate diagnosis of breast cancer is one of the major challenges in the medical field. Supervised machine learning has been used to simulate a model of the distribution of class label in terms of predictor features. The resultant classifier is then used for helping doctors' forms a...

  • Diagnosis of Breast Cancer using Decision Tree Models and SVM. Elsayad, Alaa M.; Elsalamony, H. A. // International Journal of Computer Applications;Dec2013, Vol. 83, p19 

    Breast cancer represents the second important cause of cancer deaths in women today and it is the most common type of cancer in women. Disease diagnosis is one of the applications where data mining tools are proving successful results. Data mining with decision trees is popular and effective...

  • Research on the Optimal Information Retrieval Based on SVM. Sun Jianming; Sun Qingli // International Journal of Control & Automation;2014, Vol. 7 Issue 8, p419 

    Research on the retrieval with time limitation in distributed retrieval, the optimal resource description and selection strategy is proposed with the SVM method combing the retrieval method based on topic clustering. Pre-treatment text database is treated by practicing the SVM method. The...

  • Firefly and BAYES Classifier for Email Spam Classification in a Distributed Environment. Dhanaraj, Karthika Renuka; Palaniswami, Visalakshi // Australian Journal of Basic & Applied Sciences;Nov2014, Vol. 8 Issue 17, p118 

    Background: In today's computer world, Internet plays a main role. Internet mail system is a store and forward mechanism used for the purpose of exchanging documents across computer network through Internet. Unsolicited Bulk E-mail(UBE) known as spam mail is considered to be a major threat....

  • Power Quality Disturbances Recognition Based on a Multiresolution Generalized S-Transform and a PSO-Improved Decision Tree. Nantian Huang; Shuxin Zhang; Guowei Cai; Dianguo Xu // Energies (19961073);2015, Vol. 8 Issue 1, p549 

    In a microgrid, the distributed generators (DG) can power the user loads directly. As a result, power quality (PQ) events are more likely to affect the users. This paper proposes a Multiresolution Generalized S-transform (MGST) approach to improve the ability of analyzing and monitoring the...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics