Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set

Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set Publisher Pubmed

Atashi A¹ ; Tohidinezhad F² ; Dorri S³ ; Nazeri N³ ; Ghousi R⁴ ; Marashi S¹ ; Hajialiasgari F¹

Show Affiliations

1. E-Health Department, Virtual School, Tehran University of Medical Sciences, Tehran, Iran
2. Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
3. Clinical Research Department, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran
4. School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Source: Studies in Health Technology and Informatics Published:2019

Abstract

The aim is to recognize the unknown atterns in a real breast cancer dataset using data mining algorithms as a new method in medicine. Due to excessive missing data in the collection only data on 665 of 809 patients were available. The other missing values were estimated using the EM algorithm in SPSS21 software. Fields have been converted into discrete fields and finally the APRIORI algorithm has been used to analyze and explore the unknown patterns. After the rule extraction, experts in the field of breast cancer eliminated redundant and meaningless relations. 100 association rules with a confidence value of more than 0.9 explored by the APRIORI algorithm and after the clinical expert feedback, 10 clinically meaningful relations have been detected and reported. Due to the high number of risk factors, the use of data mining is effective for cancer data. These patterns provide the future study hypotheses of specific clinical studies. © 2019 The authors and IOS Press. All rights reserved.

Style	Citing Format
MLA	Atashi A, et al.. "Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set." Studies in Health Technology and Informatics, vol. 262, no. , 2019, pp. 142-145.
APA	Atashi A, Tohidinezhad F, Dorri S, Nazeri N, Ghousi R, Marashi S, Hajialiasgari F (2019). Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set. Studies in Health Technology and Informatics, 262(), 142-145.
Chicago	Atashi A, Tohidinezhad F, Dorri S, Nazeri N, Ghousi R, Marashi S, Hajialiasgari F. "Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set." Studies in Health Technology and Informatics 262, no. (2019): 142-145.
Harvard	Atashi A et al. (2019) 'Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set', Studies in Health Technology and Informatics, 262(), pp. 142-145.
Vancouver	Atashi A, Tohidinezhad F, Dorri S, Nazeri N, Ghousi R, Marashi S, et al.. Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set. Studies in Health Technology and Informatics. 2019;262():142-145.
BibTex	@article{ author = {Atashi A and Tohidinezhad F and Dorri S and Nazeri N and Ghousi R and Marashi S and Hajialiasgari F}, title = {Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set}, journal = {Studies in Health Technology and Informatics}, volume = {262}, number = {}, pages = {142-145}, year = {2019} }
RIS	TY - JOUR AU - Atashi A AU - Tohidinezhad F AU - Dorri S AU - Nazeri N AU - Ghousi R AU - Marashi S AU - Hajialiasgari F TI - Discovery of Hidden Patterns in Breast Cancer Patients, Using Data Mining on a Real Data Set JO - Studies in Health Technology and Informatics VL - 262 IS - SP - 142 EP - 145 PY - 2019 ER -

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