{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T17:26:31Z","timestamp":1772645191195,"version":"3.50.1"},"reference-count":28,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,8,24]]},"abstract":"<jats:p>Early detection and classification of breast cancer can be facilitated to initiate the most effective treatment. As the second leading cause of death among women, early breast cancer screening is essential for reducing mortality rates. In this context, Convolutional neural networks (CNNs) are the ideal candidate for increasing the rate of identification and classification of tumours with efficiency, particularly in medical imaging. This research proposes a hybridised CNN with the Orca Predation Optimization Algorithm (OPOA) as a novel classification model for the effective detection of abnormalities in breast cancer diagnosis. Specifically, the OPOA technique is used to determine the optimal hyperparameter values for the hybrid CNN architecture being deployed. As the pretrained CNN model, the suggested model utilizeds a ResNet50 residual network. It merged OPOA with the ResNet50 residual network to construct the OPOA-ResNet-50 Architecture. The experimental validation of the proposed OPOA-ResNet-50 model utilising the datasets of curated breast imaging subset of DDSM (CBIS-DDSM) shown improved classification accuracy of 99.04%, specificity of 98.56%, and sensitivity of 97.78% in comparison to the baseline techniques. The results also revealed that the proposed under mammographic image analysis society (MIAS) OPOA-ResNet-50 model demonstrated superior classification accuracy of 98.64%, specificity of 98.79%, and sensitivity of 98.82% compared to the benchmarked methods. The adopted OPOA algorithm is determined to achieve more optimal hyperparameter values for the ResNet50 architecture than the comparative algorithms Improved Marine Predator Optimization Algorithm (IMPOA), Whale Optimization Algorithm (WOA), Harris hawk\u2019s optimization (HHO), and gravitational search algorithm (GSA).<\/jats:p>","DOI":"10.3233\/jifs-231176","type":"journal-article","created":{"date-parts":[[2023,6,20]],"date-time":"2023-06-20T11:20:40Z","timestamp":1687260040000},"page":"3855-3873","source":"Crossref","is-referenced-by-count":25,"title":["Breast cancer diagnosis using Orca predation optimization algorithm"],"prefix":"10.1177","volume":"45","author":[{"given":"P.","family":"Kaladevi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India"}]},{"given":"V.V.","family":"Punitha","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India"}]},{"given":"D.","family":"Muthusankar","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India"}]},{"given":"R.","family":"Praveen","sequence":"additional","affiliation":[{"name":"Department of Computer Technology, Madras Institute of Technology Campus, Anna University, Chennai, TamilNadu, India"}]}],"member":"179","reference":[{"issue":"1","key":"10.3233\/JIFS-231176_ref1","first-page":"77","article-title":"Breast cancer classification application based on QGA-SVM","volume":"42","author":"Dong","year":"2022","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"issue":"1","key":"10.3233\/JIFS-231176_ref2","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.3233\/JIFS-213158","article-title":"Deep-Hist: Breast cancer diagnosis through histopathological images using convolution neural network","volume":"43","author":"Iqbal","year":"2022","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"issue":"4","key":"10.3233\/JIFS-231176_ref3","doi-asserted-by":"crossref","first-page":"4205","DOI":"10.3233\/JIFS-210393","article-title":"ASU-Net: Ushape adaptive scale network for mass segmentation in mammograms","volume":"42","author":"Sun","year":"2022","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-231176_ref4","first-page":"1","article-title":"Multimodal prediction of breast cancer using radiogenomics and clinical trials with decision fusion","author":"Ramkumar","year":"2022","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-231176_ref5","doi-asserted-by":"crossref","unstructured":"Panigrahi S. , Swapnarekha H. and Subudhi S. , GACO: A Genetic Algorithm with Ant Colony Optimization\u2013Based Feature Selection for Breast Cancer Diagnosis in: Nature-Insired Optimization Methodologies in Biomedical and Healthcare, Springer, (2023), pp. 269\u2013293.","DOI":"10.1007\/978-3-031-17544-2_12"},{"key":"10.3233\/JIFS-231176_ref6","first-page":"1","article-title":"An efficient hybrid model based on modified whale optimization algorithm and multilayer perceptron neural network for medical classification problems","author":"Raziani","year":"2022","journal-title":"Journal of Bionic Engineering"},{"issue":"1","key":"10.3233\/JIFS-231176_ref7","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.bbe.2019.12.004","article-title":"Simultaneous feature weighting and parameter determination of neural networks using ant lion optimization for the classification of breast cancer","volume":"40","author":"Dalwinder","year":"2020","journal-title":"Biocybernetics and Biomedical Engineering"},{"issue":"1","key":"10.3233\/JIFS-231176_ref8","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1002\/ima.22468","article-title":"Automatic breast cancer detection based on optimized neural network using whale optimization algorithm","volume":"31","author":"Fang","year":"2021","journal-title":"International Journal of Imaging Systems and Technology"},{"key":"10.3233\/JIFS-231176_ref9","doi-asserted-by":"crossref","first-page":"106958","DOI":"10.1016\/j.compeleceng.2020.106958","article-title":"An automated breast cancer diagnosis using feature selection and parameter optimization in ANN","volume":"90","author":"Punitha","year":"2021","journal-title":"Computers & Electrical Engineering"},{"issue":"1","key":"10.3233\/JIFS-231176_ref10","doi-asserted-by":"publisher","first-page":"149","DOI":"10.3233\/JIFS-221615","article-title":"An improved ensemble classification-based secure two stage bagging pruning technique for guaranteeing privacy preservation of DNA sequences in electronic health records","volume":"44","author":"Kaladevi","year":"2023","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-231176_ref11","doi-asserted-by":"crossref","unstructured":"Khan M.M. , Tazin T. , Hussain M. 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