Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Breast Cancer Detection in Mammography Images Using Deep Convolutional Neural Networks and Fuzzy Ensemble Modeling Techniques Subject The topic of the resource breast cancer; deep CNN; DenseNet121; ensemble; fuzzy; Gompertzfunction; Inception V4; ResNet-164; VGG-11 Description An account of the resource Breast cancer has evolved as the most lethal illness impacting women all over the globe. Breast cancer may be detected early, which reduces mortality and increases the chances of a full recovery. Researchers all around the world are working on breast cancer screening tools based on medical imaging. Deep learning approaches have piqued the attention of many in the medical imaging field due to their rapid growth. In this research, mammography pictures were utilized to detect breast cancer. We have used four mammography imaging datasets with a similar number of 1145 normal, benign, and malignant pictures using various deep CNN (Inception V4, ResNet-164, VGG-11, and DenseNet121) models as base classifiers. The proposed technique employs an ensemble approach in which the Gompertz function is used to build fuzzy rankings of the base classification techniques, and the decision scores of the base models are adaptively combined to construct final predictions. The proposed fuzzy ensemble techniques outperform each individual transfer learning methodology as well as multiple advanced ensemble strategies (Weighted Average, Sugeno Integral) with reference to prediction and accuracy. The suggested Inception V4 ensemble model with fuzzy rank based Gompertz function has a 99.32% accuracy rate. We believe that the suggested approach will be of tremendous value to healthcare practitioners in identifying breast cancer patients early on, perhaps leading to an immediate diagnosis. 2022 by the authors. Creator An entity primarily responsible for making the resource Altameem A.; Mahanty C.; Poonia R.C.; Saudagar A.K.J.; Kumar R. Source A related resource from which the described resource is derived Diagnostics, Vol-12, No. 8 Publisher An entity responsible for making the resource available Multidisciplinary Digital Publishing Institute (MDPI) Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3390/diagnostics12081812" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/diagnostics12081812</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137404869&amp;doi=10.3390%2Fdiagnostics12081812&amp;partnerID=40&amp;md5=eccc4042fccd07e514cff67c3508b976" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137404869&amp;doi=10.3390%2fdiagnostics12081812&amp;partnerID=40&amp;md5=eccc4042fccd07e514cff67c3508b976</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20754418 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Altameem A., Department of Computer Science and Engineering, College of Applied Studies and Community Services, King Saud University, Riyadh, 11533, Saudi Arabia; Mahanty C., Department of Computer Science and Engineering, GIET University, Odisha 765022, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Saudagar A.K.J., Information Systems Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Kumar R., Department of Computer Science and Engineering, GIET University, Odisha 765022, India