{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T22:44:32Z","timestamp":1778712272324,"version":"3.51.4"},"reference-count":18,"publisher":"IGI Global","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10,1]]},"abstract":"<p>Breast cancer has become a major health problem in the world over the past 50 years and its incidence has increased in recent years. It accounts for 33% of all cancer cases, and 60% of new cases of breast cancer occur in women aged 50 to 74 years. In this work we have proposed a computer-assisted diagnostic (CAD) system that can predict whether a woman has cancer or not by analyzing her mammogram automatically without passing through a biopsy stage. The screening mammogram will be vectorized using the n-gram pixel representation. After the vectors obtained will be classified into one of the classes\u2014with cancer or without cancer\u2014using the social elephant algorithm. The experimentation using the digital database for screening mammography (DDSM) and validation measures\u2014f-measure entropy recall, accuracy, specificity, RCT, ROC, AUC\u2014show clearly the effectiveness and the superiority of our proposed bioinspired technique compared to others techniques existed in the literature such as na\u00efve bayes, Knearest neighbours, and decision tree c4.5. The goal is to help radiologists with early detection to reduce the mortality rate among women with breast cancer.<\/p>","DOI":"10.4018\/ijssci.2019100103","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T19:05:20Z","timestamp":1579287920000},"page":"31-49","source":"Crossref","is-referenced-by-count":7,"title":["A Computer-Assisted Diagnostic (CAD) of Screening Mammography to Detect Breast Cancer Without a Surgical Biopsy"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4973-4385","authenticated-orcid":true,"given":"Hadj Ahmed","family":"Bouarara","sequence":"first","affiliation":[{"name":"GeCoDe Laboratory, Dr. Moulay Tahar Universit\u00e9 de Saida, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJSSCI.2019100103-0","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0177544"},{"key":"IJSSCI.2019100103-1","doi-asserted-by":"publisher","DOI":"10.3322\/canjclin.32.4.194"},{"key":"IJSSCI.2019100103-2","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON.2015.7372809"},{"key":"IJSSCI.2019100103-3","unstructured":"Chaurasia, V., & Pal, S. (2017). A novel approach for breast cancer detection using data mining techniques."},{"key":"IJSSCI.2019100103-4","unstructured":"Chaurasia, V., & Pal, S. (2017). A novel approach for breast cancer detection using data mining techniques."},{"key":"IJSSCI.2019100103-5","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(96)02133-2"},{"key":"IJSSCI.2019100103-6","first-page":"252","article-title":"SVM-Kmeans: Support Vector Machine based on Kmeans clustering for breast cancer diagnosis. Int. J.","volume":"5","author":"W.Gad","year":"2016","journal-title":"Computer and Information Technology"},{"key":"IJSSCI.2019100103-7","doi-asserted-by":"publisher","DOI":"10.1109\/CFIS.2018.8336649"},{"issue":"6","key":"IJSSCI.2019100103-8","first-page":"315","article-title":"Diagnosis and prognosis breast cancer using classification rules.","volume":"2","author":"J.Joshi","year":"2014","journal-title":"International Journal of Engineering Research and General Science"},{"key":"IJSSCI.2019100103-9","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.11.219"},{"key":"IJSSCI.2019100103-10","doi-asserted-by":"publisher","DOI":"10.1109\/IRI.2011.6009538"},{"key":"IJSSCI.2019100103-11","doi-asserted-by":"publisher","DOI":"10.1373\/clinchem.2015.238691"},{"key":"IJSSCI.2019100103-12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2014.09.020"},{"key":"IJSSCI.2019100103-13","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2012.10.006"},{"issue":"569","key":"IJSSCI.2019100103-14","first-page":"2","article-title":"Breast cancer diagnosis on three different datasets using multi-classifiers.","volume":"32","author":"G. I.Salama","year":"2012","journal-title":"Breast Cancer (Tokyo, Japan)"},{"issue":"10","key":"IJSSCI.2019100103-15","article-title":"Diagnosis of breast cancer using decision tree data mining technique.","volume":"98","author":"R.Sumbaly","year":"2014","journal-title":"International Journal of Computers and Applications"},{"key":"IJSSCI.2019100103-16","doi-asserted-by":"publisher","DOI":"10.1038\/nature06487"},{"issue":"4","key":"IJSSCI.2019100103-17","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1093\/clinchem\/39.4.561","article-title":"Receiver-operating characteristic (ROC) plots: A fundamental evaluation tool in clinical medicine.","volume":"39","author":"M. H.Zweig","year":"1993","journal-title":"Clinical Chemistry"}],"container-title":["International Journal of Software Science and Computational Intelligence"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=247134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T01:52:17Z","timestamp":1651888337000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJSSCI.2019100103"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2019,10,1]]},"references-count":18,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,10]]}},"URL":"https:\/\/doi.org\/10.4018\/ijssci.2019100103","relation":{},"ISSN":["1942-9045","1942-9037"],"issn-type":[{"value":"1942-9045","type":"print"},{"value":"1942-9037","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,1]]}}}