{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T07:03:53Z","timestamp":1779865433458,"version":"3.53.1"},"reference-count":66,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.bspc.2026.110411","type":"journal-article","created":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T09:19:44Z","timestamp":1778404784000},"page":"110411","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["CCNN: Concatenation-based convolutional neural network for multimodal breast cancer diagnosis"],"prefix":"10.1016","volume":"123","author":[{"given":"Preeti Pandurang","family":"kale","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sujata","family":"Kulkarni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hemant","family":"Mahajan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shailaja N.","family":"Uke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aparna","family":"Junnarkar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shilpa","family":"Pawar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharayu","family":"Lokhande","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0974-3853","authenticated-orcid":false,"given":"Sulbha","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"23","key":"10.1016\/j.bspc.2026.110411_b0005","first-page":"2483","volume":"12","author":"Song","year":"2024","journal-title":"Rare Breast Cancers Review. Healthcare"},{"issue":"17","key":"10.1016\/j.bspc.2026.110411_b0010","doi-asserted-by":"crossref","first-page":"4287","DOI":"10.3390\/cancers13174287","article-title":"Breast cancer\u2014epidemiology, risk factors, classification, Prognostic markers, and Current Treatment Strategies\u2014an Updated Review","volume":"13","author":"\u0141ukasiewicz","year":"2021","journal-title":"Cancers"},{"key":"10.1016\/j.bspc.2026.110411_b0015","doi-asserted-by":"crossref","unstructured":"Shaikh, K., Krishnan, S., Thanki, R. (2021). An Introduction to Breast Cancer. In: Artificial Intelligence in Breast Cancer Early Detection and Diagnosis. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-59208-0_1.","DOI":"10.1007\/978-3-030-59208-0"},{"issue":"10","key":"10.1016\/j.bspc.2026.110411_b0020","doi-asserted-by":"crossref","first-page":"2569","DOI":"10.3390\/cancers14102569","article-title":"Breast Cancer\u2014Epidemiology, Classification, Pathogenesis and Treatment (Review of Literature)","volume":"14","author":"Smolarz","year":"2022","journal-title":"Cancers"},{"issue":"8","key":"10.1016\/j.bspc.2026.110411_b0025","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.3390\/cancers16081583","article-title":"Causes and Risk Factors of Breast Cancer, what do we know for sure? an evidence Synthesis of Systematic Reviews and Meta-analyses","volume":"16","author":"orghild L\u00f8yland, Ida Hellum Sandbekken, Ellen Karine Grov, & Utne, I.","year":"2024","journal-title":"Cancers"},{"issue":"14","key":"10.1016\/j.bspc.2026.110411_b0030","doi-asserted-by":"crossref","first-page":"2460","DOI":"10.3390\/diagnostics13142460","article-title":"A Review of Machine Learning Techniques for the Classification and Detection of Breast Cancer from Medical Images","volume":"13","author":"Jalloul","year":"2023","journal-title":"Diagnostics"},{"key":"10.1016\/j.bspc.2026.110411_b0035","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/s40659-017-0140-9","article-title":"Awareness and current knowledge of breast cancer","volume":"50","author":"Akram","year":"2017","journal-title":"Biol. Res."},{"key":"10.1016\/j.bspc.2026.110411_b0040","doi-asserted-by":"crossref","unstructured":"Cheng, H.D., Hu, Y.G., Hung, D.L., Wu, C.Y. (2002). Breast Cancer Classification Using Fuzzy Central Moments. In: Barro, S., Mar\u00edn, R. (eds) Fuzzy Logic in Medicine. Studies in Fuzziness and Soft Computing, vol 83. Physica, Heidelberg. https:\/\/doi.org\/10.1007\/978-3-7908-1804-8_3.","DOI":"10.1007\/978-3-7908-1804-8_3"},{"issue":"11","key":"10.1016\/j.bspc.2026.110411_b0045","doi-asserted-by":"crossref","first-page":"2764","DOI":"10.3390\/cancers13112764","article-title":"A Review of Computer-aided Expert Systems for Breast Cancer Diagnosis","volume":"13","author":"Liew","year":"2021","journal-title":"Cancers"},{"key":"10.1016\/j.bspc.2026.110411_b0050","first-page":"1","article-title":"Machine-learning methods in detecting breast cancer and related therapeutic issues: a review. Computer Methods in Biomechanics and Biomedical Engineering","author":"Jafari","year":"2024","journal-title":"Imaging & Visualization"},{"issue":"2","key":"10.1016\/j.bspc.2026.110411_b0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.imed.2021.08.004","article-title":"Comparative Analysis of Breast Cancer detection using Machine Learning and Biosensors","volume":"2","author":"Amethiya","year":"2021","journal-title":"Intelligent Medicine"},{"issue":"1063\/5","key":"10.1016\/j.bspc.2026.110411_b0060","article-title":"Literature review of breast cancer detection using machine learning algorithms","volume":"10","author":"Abunasser","year":"2023","journal-title":"Nucleation and Atmospheric Aerosols. Doi"},{"key":"10.1016\/j.bspc.2026.110411_b0065","first-page":"168","article-title":"Breast Cancer Detection with Machine Learning-a Review","volume":"2022","author":"Meghana","year":"2023","journal-title":"International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)"},{"issue":"22","key":"10.1016\/j.bspc.2026.110411_b0070","doi-asserted-by":"crossref","first-page":"8298","DOI":"10.3390\/app10228298","article-title":"Deep-Learning-based Computer-aided Systems for Breast Cancer Imaging: a critical Review","volume":"10","author":"Jim\u00e9nez-Gaona","year":"2020","journal-title":"Appl. Sci."},{"key":"10.1016\/j.bspc.2026.110411_b0075","series-title":"Handbook of Oncobiology: from Basic to Clinical Sciences","article-title":"Deep Learning Techniques for Computer aided Diagnosis of Various Cancers","author":"Aggarwal","year":"2023"},{"key":"10.1016\/j.bspc.2026.110411_b0080","article-title":"A dynamic Bi-CSAM-Net for brain tumor segmentation","volume":"112","author":"Asimeng","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.bspc.2026.110411_b0085","doi-asserted-by":"crossref","unstructured":"Barsha Abhisheka, Saroj Kumar Biswas, & Biswajit Purkayastha. (2023). A Comprehensive Review on Breast Cancer Detection, Classification and Segmentation Using Deep Learning. Archives of Computational Methods in Engineering. https:\/\/doi.org\/10.1007\/s11831-023-09968-z.","DOI":"10.1007\/s11831-023-09968-z"},{"key":"10.1016\/j.bspc.2026.110411_b0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejmp.2023.103138","article-title":"Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms","volume":"114","author":"Sahu","year":"2023","journal-title":"Phys. Med."},{"key":"10.1016\/j.bspc.2026.110411_b0095","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1186\/s13058-024-01895-6","article-title":"Deep learning applications in breast cancer histopathological imaging: diagnosis, treatment, and prognosis","volume":"26","author":"Jiang","year":"2024","journal-title":"Breast Cancer Res."},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0100","first-page":"161","article-title":"Deep Learning based Methods for Breast Cancer Diagnosis: a Systematic Review and Future direction","volume":"13","author":"Nasser","year":"2023","journal-title":"Diagnostics (basel, Switzerland)"},{"key":"10.1016\/j.bspc.2026.110411_b0105","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1186\/s12880-024-01402-5","article-title":"The BCPM method: decoding breast cancer with machine learning","volume":"24","author":"Almarri","year":"2024","journal-title":"BMC Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110411_b0110","article-title":"Deep learning algorithms for the early detection of breast cancer: a comparative study with traditional machine learning","volume":"41","author":"Gonzales Martinez","year":"2023","journal-title":"Inf. Med. Unlocked"},{"key":"10.1016\/j.bspc.2026.110411_b0115","doi-asserted-by":"crossref","DOI":"10.1155\/2019\/4253641","article-title":"Automated Breast Cancer Diagnosis based on Machine Learning Algorithms","volume":"2019","author":"Dhahri","year":"2019","journal-title":"Journal of Healthcare Engineering"},{"key":"10.1016\/j.bspc.2026.110411_b0120","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.ijmedinf.2019.05.003","article-title":"Predicting breast cancer metastasis by using serum biomarkers and clinicopathological data with machine learning technologies","volume":"128","author":"Tseng","year":"2019","journal-title":"Int. J. Med. Inf."},{"key":"10.1016\/j.bspc.2026.110411_b0125","doi-asserted-by":"crossref","first-page":"106198","DOI":"10.1109\/ACCESS.2020.3000075","article-title":"Application of Machine Learning and Word Embeddings in the Classification of Cancer Diagnosis using Patient Anamnesis","volume":"8","author":"Magna","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0130","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.jmir.2019.11.001","article-title":"Machine Learning Methods for Computer-aided Breast Cancer Diagnosis using Histopathology: a Narrative Review","volume":"51","author":"Saxena","year":"2020","journal-title":"Journal of Medical Imaging and Radiation Sciences"},{"key":"10.1016\/j.bspc.2026.110411_b0135","series-title":"2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","article-title":"A Stack based Multimodal Machine Learning Model for Breast Cancer Diagnosis","author":"Kayikci","year":"2022"},{"issue":"12","key":"10.1016\/j.bspc.2026.110411_b0140","doi-asserted-by":"crossref","first-page":"10473","DOI":"10.1007\/s00432-023-04956-z","article-title":"Machine learning and deep learning techniques for breast cancer diagnosis and classification: a comprehensive review of medical imaging studies","volume":"149","author":"Radak","year":"2023","journal-title":"J. Cancer Res. Clin. Oncol."},{"issue":"2","key":"10.1016\/j.bspc.2026.110411_b0145","doi-asserted-by":"crossref","first-page":"575","DOI":"10.32628\/CSEIT2410274","article-title":"Breast Cancer Classification using Machine Learning","volume":"10","author":"Ankit","year":"2024","journal-title":"International Journal of Scientific Research in Computer Science Engineering and Information Technology"},{"key":"10.1016\/j.bspc.2026.110411_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.106951","article-title":"Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning","volume":"223","author":"Aljuaid","year":"2022","journal-title":"Comput. Methods Programs Biomed."},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0155","doi-asserted-by":"crossref","DOI":"10.1186\/s40537-023-00749-w","article-title":"Breast cancer prediction using gated attentive multimodal deep learning","volume":"10","author":"Kayikci","year":"2023","journal-title":"Journal of Big Data"},{"key":"10.1016\/j.bspc.2026.110411_b0160","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.ijin.2023.02.001","article-title":"Efficient breast cancer detection via cascade deep learning network","volume":"4","author":"Asadi","year":"2023","journal-title":"International Journal of Intelligent Networks"},{"issue":"12","key":"10.1016\/j.bspc.2026.110411_b0165","doi-asserted-by":"crossref","first-page":"2222","DOI":"10.3390\/cancers16122222","article-title":"Ensemble Deep Learning-based image Classification for Breast Cancer Subtype and Invasiveness Diagnosis from whole Slide image Histopathology","volume":"16","author":"Balasubramanian","year":"2024","journal-title":"Cancers"},{"issue":"8","key":"10.1016\/j.bspc.2026.110411_b0170","doi-asserted-by":"crossref","first-page":"792","DOI":"10.3390\/jpm14080792","article-title":"Breast Cancer Detection and Analytics using Hybrid CNN and Extreme Learning Machine","volume":"14","author":"Sureshkumar","year":"2024","journal-title":"Journal of Personalized Medicine"},{"issue":"5","key":"10.1016\/j.bspc.2026.110411_b0175","doi-asserted-by":"crossref","first-page":"3759","DOI":"10.1007\/s00521-024-10790-2","article-title":"Efficient breast cancer detection using neural networks and explainable artificial intelligence","volume":"37","author":"Murugan","year":"2024","journal-title":"Neural Comput. & Applic."},{"key":"10.1016\/j.bspc.2026.110411_b0180","doi-asserted-by":"crossref","unstructured":"R, M. T., Thakur, A., Gupta, M., Deepak Kumar Sinha, Kritika Kumari Mishra, Vinoth Kumar Venkatesan, & Suresh Guluwadi. (2024). Transformative Breast Cancer Diagnosis using CNNs with Optimized ReduceLROnPlateau and Early Stopping Enhancements. \u0303the \u0153International Journal of Computational Intelligence Systems\/International Journal of Computational Intelligence Systems, 17(1). https:\/\/doi.org\/10.1007\/s44196-023-00397-1.","DOI":"10.1007\/s44196-023-00397-1"},{"issue":"4","key":"10.1016\/j.bspc.2026.110411_b0185","doi-asserted-by":"crossref","first-page":"2338","DOI":"10.3390\/biomedinformatics4040127","article-title":"Early Breast Cancer Detection based on Deep Learning: an Ensemble Approach Applied to Mammograms","volume":"4","author":"Khourdifi","year":"2024","journal-title":"BioMedInformatics"},{"issue":"7","key":"10.1016\/j.bspc.2026.110411_b0190","doi-asserted-by":"crossref","first-page":"80","DOI":"10.3390\/bdcc8070080","article-title":"Breast Cancer Detection and Localizing the Mass Area using Deep Learning","volume":"8","author":"Mijanur Rahman","year":"2024","journal-title":"Big Data and Cognitive Computing"},{"issue":"11","key":"10.1016\/j.bspc.2026.110411_b0195","doi-asserted-by":"crossref","first-page":"294","DOI":"10.3390\/computers13110294","article-title":"Deep Learning based Breast Cancer Detection using Decision Fusion","volume":"13","author":"Manal\u0131","year":"2024","journal-title":"Computers"},{"issue":"13","key":"10.1016\/j.bspc.2026.110411_b0200","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.3390\/diagnostics14131402","article-title":"Attention-based Deep Learning Approach for Breast Cancer Histopathological image Multi-Classification","volume":"14","author":"Aldakhil","year":"2024","journal-title":"Diagnostics"},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0205","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-73083-7","article-title":"Feature-based detection of breast cancer using convolutional neural network and feature engineering","volume":"14","author":"Essa","year":"2024","journal-title":"Sci. Rep."},{"issue":"7","key":"10.1016\/j.bspc.2026.110411_b0210","doi-asserted-by":"crossref","DOI":"10.1007\/s42979-024-03197-2","article-title":"Enhancing Breast Cancer Detection through a Tailored Convolutional Neural Network Deep Learning Approach","volume":"5","author":"Kunta","year":"2024","journal-title":"SN Comput. Sci."},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0215","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1109\/JBHI.2023.3283042","article-title":"Collaborative transfer Network for Multi-Classification of Breast Cancer Histopathological Images","volume":"28","author":"Liu","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.bspc.2026.110411_b0220","article-title":"ADBNet: an Attention-Guided Deep Broad Convolutional Neural Network for the Classification of Breast Cancer Histopathology Images","volume":"1\u20131","author":"Rahman","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0225","doi-asserted-by":"crossref","first-page":"87560","DOI":"10.1109\/ACCESS.2024.3415482","article-title":"Automated Identification of Breast Cancer Type using Novel Multipath transfer Learning and Ensemble of Classifier","volume":"12","author":"Nair","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0230","doi-asserted-by":"crossref","first-page":"70825","DOI":"10.1109\/ACCESS.2024.3401729","article-title":"FastLeakyResNet-CIR: a Novel Deep Learning Framework for Breast Cancer Detection and Classification","volume":"12","author":"Zeng","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0235","doi-asserted-by":"crossref","first-page":"184119","DOI":"10.1109\/ACCESS.2024.3503413","article-title":"Hybrid Deep Learning EfficientNetV2 and Vision Transformer (EffNetV2-ViT) Model for Breast Cancer Histopathological image Classification","volume":"12","author":"Hayat","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0240","doi-asserted-by":"crossref","first-page":"55595","DOI":"10.1109\/ACCESS.2021.3071766","article-title":"A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial internet of things","volume":"9","author":"Huma","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0245","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-81308-5_16","article-title":"Breast Cancer Detection using Thermography and Convolutional Neural Networks (CNNs)","volume":"169\u2013181","author":"Sayed","year":"2025","journal-title":"Lecture Notes on Data Engineering and Communications Technologies"},{"key":"10.1016\/j.bspc.2026.110411_b0250","article-title":"Enhancing Breast Cancer Diagnosis with Bidirectional Recurrent Neural Networks: a Novel Approach for Histopathological image Multi-Classification","volume":"1\u20131","author":"Chikkala","year":"2025","journal-title":"IEEE Access"},{"key":"10.1016\/j.bspc.2026.110411_b0255","article-title":"Self-DenseMobileNet: a robust framework for lung nodule classification using Self-ONN and stacking-based meta-classifier","volume":"112","author":"Rahman","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"issue":"3","key":"10.1016\/j.bspc.2026.110411_b0260","doi-asserted-by":"crossref","first-page":"142","DOI":"10.3390\/bdcc7030142","article-title":"Breast Cancer Classification using Concatenated Triple Convolutional Neural Networks Model","volume":"7","author":"Alshayeji","year":"2023","journal-title":"Big Data and Cognitive Computing"},{"key":"10.1016\/j.bspc.2026.110411_b0265","doi-asserted-by":"crossref","DOI":"10.1016\/j.apacoust.2023.109759","article-title":"Concatenation-based pre-trained convolutional neural networks using attention mechanism for environmental sound classification","volume":"216","author":"Ashurov","year":"2024","journal-title":"Appl. Acoust."},{"key":"10.1016\/j.bspc.2026.110411_b0270","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.media.2019.05.010","article-title":"BACH: Grand challenge on breast cancer histology images","volume":"56","author":"Aresta","year":"2019","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.bspc.2026.110411_b0275","article-title":"Dataset of Breast mammography images with Masses","volume":"2","author":"Lin","year":"2020","journal-title":"Data.mendeley.com"},{"key":"10.1016\/j.bspc.2026.110411_b0280","article-title":"Mammographic image Analysis Society (MIAS) database v1.21","author":"Suckling","year":"2015","journal-title":"Cam.ac.uk"},{"issue":"2","key":"10.1016\/j.bspc.2026.110411_b0285","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.acra.2011.09.014","article-title":"INbreast: toward a full-field digital mammographic database","volume":"19","author":"Moreira","year":"2012","journal-title":"Acad. Radiol."},{"key":"10.1016\/j.bspc.2026.110411_b0290","doi-asserted-by":"crossref","DOI":"10.1038\/sdata.2017.177","article-title":"A curated mammography data set for use in computer-aided detection and diagnosis research","volume":"4","author":"Lee","year":"2017","journal-title":"Sci. Data"},{"issue":"1","key":"10.1016\/j.bspc.2026.110411_b0295","article-title":"A new hybrid image denoising algorithm using adaptive and modified decision-based filters for enhanced image quality","volume":"15","author":"Ullah","year":"2025","journal-title":"Sci. Rep."},{"issue":"2","key":"10.1016\/j.bspc.2026.110411_b0300","article-title":"COMPARATIVE ANALYSIS REVIEW OF ADAPTIVE NON-LINEAR HYBRID FILTER AND TRADITIONAL FILTERING TECHNIQUES","volume":"14","author":"Pratap","year":"2026","journal-title":"IJCRT - International Journal of Creative Research Thoughts (IJCRT)"},{"issue":"6","key":"10.1016\/j.bspc.2026.110411_b0305","doi-asserted-by":"crossref","DOI":"10.1140\/epjp\/s13360-021-01693-5","article-title":"Adaptive denoising for strong noisy images by using positive effects of noise. the","volume":"136","author":"Shen","year":"2021","journal-title":"European Physical Journal plus"},{"issue":"13","key":"10.1016\/j.bspc.2026.110411_b0310","doi-asserted-by":"crossref","first-page":"5776","DOI":"10.3390\/s23135776","article-title":"Local Adaptive image Filtering based on Recursive Dilation Segmentation","volume":"23","author":"Zhang","year":"2023","journal-title":"Sensors"},{"issue":"14","key":"10.1016\/j.bspc.2026.110411_b0315","doi-asserted-by":"crossref","first-page":"4287","DOI":"10.3390\/s25144287","article-title":"Adaptive Guided Filtering and Spectral-Entropy-based Non-Uniformity Correction for High-Resolution Infrared Line-Scan Images","volume":"25","author":"Huang","year":"2025","journal-title":"Sensors"},{"key":"10.1016\/j.bspc.2026.110411_b0320","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-96-5723-0_3","article-title":"Adaptive image Denoising using Expectation\u2013Maximization Algorithm","volume":"33\u201344","author":"Sathya","year":"2025","journal-title":"Lecture Notes in Networks and Systems"},{"key":"10.1016\/j.bspc.2026.110411_b0325","article-title":"Introduction to Breast Cancer","volume":"1\u201322","author":"Mir","year":"2023","journal-title":"Therapeutic Potential of Cell Cycle Kinases in Breast Cancer"},{"key":"10.1016\/j.bspc.2026.110411_b0330","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-70875-6_1","article-title":"A Guide to Breast Cancer Research: an Introduction","volume":"1\u20135","author":"Clarke","year":"2025","journal-title":"Adv. Exp. Med. Biol."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426009651?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426009651?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T06:20:56Z","timestamp":1779862856000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426009651"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":66,"alternative-id":["S1746809426009651"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110411","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CCNN: Concatenation-based convolutional neural network for multimodal breast cancer diagnosis","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110411","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110411"}}