BC-SwinNet: Swin transformer and CNN with multi-objective optimization for multi-class breast cancer detection using Histopathological images.

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Title: BC-SwinNet: Swin transformer and CNN with multi-objective optimization for multi-class breast cancer detection using Histopathological images.
Authors: Khan M; Department of Informatics and Computer Systems, College of Computer Science, King Khalid University, Abha, Saudi Arabia., Altaf M; Disability Research Institute, Health Sector, King Abdulaziz City for Science and Technology, Riyadh, Kingdom of Saudi Arabia., Khan NR; Department of Computer Science & Engineering, Oriental College of Technology, Bhopal, India., Pk H; Senior Lecturer, School of Computing and Engineering, University of West London - RAK Branch Campus, Ras Al-Khaimah, UAE., Malik V; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, Patiala, India., Menshawi A; Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia., Alsubait T; Department of Computer Science and Artificial Intelligence, College of Computing, Umm Al-Qura University, Makkah, 21955, Saudi Arabia., Ziar RA; Dean, Faculty of Computer science, Kardan University, Kabul, Afghanistan. r.ziar@kardan.edu.af., Martin RJ; Faculty of Computer Science and Information Technology, Jazan University, Jazan, Saudi Arabia.
Source: Scientific reports [Sci Rep] 2026 May 11; Vol. 16 (1). Date of Electronic Publication: 2026 May 11.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-51698-2