{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:46:20Z","timestamp":1786977980848,"version":"build-2736575974"},"reference-count":33,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2017,11,16]],"date-time":"2017-11-16T00:00:00Z","timestamp":1510790400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Microscopy Res &amp; Technique"],"published-print":{"date-parts":[[2018,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Early screening of skeptical masses or breast carcinomas in mammograms is supposed to decline the mortality rate among women. This amount can be decreased more on development of the computer\u2010aided diagnosis with reduction of false suppositions in medical informatics. Our aim is to provide a robust tumor detection system for accurate classification of breast masses using normal, abnormal, benign, or malignant classes. The breast carcinomas are classified on the basis of observed classes. This is highly dependent on feature extraction process. In propose work, a novel algorithm for classification based on the combination of top Hat transformation and gray level co\u2010occurrence matrix with back propagation neural network. The aim of this study is to present a robust classification model for automated diagnosis of the breast tumor with reduction of false assumptions in medical informatics. The proposed method is verified on two datasets MIAS and DDSM. It is observed that rate of false positives decreased by the proposed method to improve the performance of classification, efficiently.<\/jats:p>","DOI":"10.1002\/jemt.22961","type":"journal-article","created":{"date-parts":[[2017,11,16]],"date-time":"2017-11-16T00:12:44Z","timestamp":1510791164000},"page":"171-180","source":"Crossref","is-referenced-by-count":86,"title":["A novel classification scheme to decline the mortality rate among women due to breast tumor"],"prefix":"10.1002","volume":"81","author":[{"given":"Bushra","family":"Mughal","sequence":"first","affiliation":[{"name":"Department of Computer Science COMSATS Institute of Information Technology Wah Cantt Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Sharif","sequence":"additional","affiliation":[{"name":"Department of Computer Science COMSATS Institute of Information Technology Wah Cantt Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4056-9854","authenticated-orcid":false,"given":"Nazeer","family":"Muhammad","sequence":"additional","affiliation":[{"name":"Department of Mathematics COMSATS Institute of Information Technology Wah Cantt Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanzila","family":"Saba","sequence":"additional","affiliation":[{"name":"College of Computer and Information Sciences Prince Sultan University Riyadh, 11586 Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2017,11,16]]},"reference":[{"issue":"3","key":"e_1_2_5_2_1","doi-asserted-by":"crossref","first-page":"176","DOI":"10.5121\/ijcsit.2011.3312","article-title":"Detection of masses in digital mammogram using second order statistics and artificial neural network","volume":"3","author":"Al Mutaz M. 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Mammographic mass classification using wavelet based support vector machine.Methods 10 11."},{"issue":"6","key":"e_1_2_5_12_1","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1016\/j.compbiomed.2013.03.008","article-title":"Mammographical mass detection and classification using local seed region growing\u2013spherical wavelet transform (lsrg\u2013swt) hybrid scheme","volume":"43","author":"G\u00f6rgel P.","year":"2013","journal-title":"Computers in Biology and Medicine"},{"key":"e_1_2_5_13_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.gco.0000192965.29449.da"},{"key":"e_1_2_5_14_1","doi-asserted-by":"crossref","unstructured":"Islam M. J. Ahmadi M. &Sid\u2010Ahmed M. 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