{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T04:12:46Z","timestamp":1790309566832,"version":"4.1.0"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers in Biology and Medicine"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.compbiomed.2026.111663","type":"journal-article","created":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T07:18:37Z","timestamp":1775200717000},"page":"111663","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":3,"special_numbering":"C","title":["A computational framework for Alzheimer's disease detection using SwinRes Transformer"],"prefix":"10.1016","volume":"208","author":[{"given":"M.","family":"Parameswari","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"N.","family":"Deepa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J.","family":"Sathya Priya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K.","family":"Muthulakshmi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"4","key":"10.1016\/j.compbiomed.2026.111663_bib1","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuri.2022.100066","article-title":"Alzheimer's disease detection from structural MRI using conditional deep triplet network","volume":"2","author":"Orouskhani","year":"2022","journal-title":"Neuroscience Informatics"},{"key":"10.1016\/j.compbiomed.2026.111663_bib2","doi-asserted-by":"crossref","first-page":"31701","DOI":"10.1109\/ACCESS.2025.3542458","article-title":"Gradual variation-based dual-stream deep learning for spatial feature enhancement with dimensionality reduction in early Alzheimer's disease detection","volume":"13","author":"Hassan","year":"2025","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111663_bib3","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-025-94677-9","article-title":"Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images","volume":"15","author":"Oraby","year":"2025","journal-title":"Sci. Rep."},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111663_bib4","doi-asserted-by":"crossref","first-page":"5815","DOI":"10.1038\/s41598-025-85703-x","article-title":"Stacked CNN-based multichannel attention networks for Alzheimer disease detection","volume":"15","author":"Hassan","year":"2025","journal-title":"Sci. Rep."},{"issue":"21","key":"10.1016\/j.compbiomed.2026.111663_bib5","doi-asserted-by":"crossref","first-page":"2363","DOI":"10.3390\/diagnostics14212363","article-title":"A feature-fusion technique-based Alzheimer's disease classification using magnetic resonance imaging","volume":"14","author":"Sait","year":"2024","journal-title":"Diagnostics"},{"key":"10.1016\/j.compbiomed.2026.111663_bib6","article-title":"Alzheimer disease classification using optimal clustering based pre-trained SqueezeNet model","volume":"100","author":"Rani","year":"2025","journal-title":"Biomed. Signal Process Control"},{"issue":"6","key":"10.1016\/j.compbiomed.2026.111663_bib7","doi-asserted-by":"crossref","first-page":"789","DOI":"10.3390\/diagnostics15060789","article-title":"A novel diagnostic framework with an optimized ensemble of vision transformers and convolutional neural networks for enhanced Alzheimer's disease detection in medical imaging","volume":"15","author":"Chakra Bortty","year":"2025","journal-title":"Diagnostics"},{"issue":"1","key":"10.1016\/j.compbiomed.2026.111663_bib8","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1007\/s11571-025-10232-2","article-title":"Classification for Alzheimer's disease and frontotemporal dementia via resting-state electroencephalography-based coherence and convolutional neural network","volume":"19","author":"Jiang","year":"2025","journal-title":"Cognitive Neurodynamics"},{"issue":"2","key":"10.1016\/j.compbiomed.2026.111663_bib9","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1097\/JCMA.0000000000001188","article-title":"Comparison of machine learning algorithms for automatic prediction of Alzheimer disease","volume":"88","author":"Aslan","year":"2025","journal-title":"J. Chin. Med. Assoc."},{"issue":"9","key":"10.1016\/j.compbiomed.2026.111663_bib10","doi-asserted-by":"crossref","first-page":"6915","DOI":"10.1007\/s00521-025-10994-0","article-title":"An effective deep learning-based automatic prediction and classification of Alzheimer's disease using EGELU-SZN technique","volume":"37","author":"Sathyabhama","year":"2025","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.compbiomed.2026.111663_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2025.110095","article-title":"Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI","volume":"190","author":"Muksimova","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.compbiomed.2026.111663_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.ibmed.2025.100219","article-title":"Optimizing ResNet50 performance using stochastic gradient descent on MRI images for Alzheimer's disease classification","volume":"11","author":"Mahjoubi","year":"2025","journal-title":"Intelligence-Based Medicine"},{"issue":"15","key":"10.1016\/j.compbiomed.2026.111663_bib13","doi-asserted-by":"crossref","first-page":"2489","DOI":"10.3390\/diagnostics13152489","article-title":"An efficient ensemble approach for Alzheimer's disease detection using an adaptive synthetic technique and deep learning","volume":"13","author":"Mujahid","year":"2023","journal-title":"Diagnostics"},{"issue":"10","key":"10.1016\/j.compbiomed.2026.111663_bib14","doi-asserted-by":"crossref","first-page":"12939","DOI":"10.1007\/s11042-018-6267-z","article-title":"Multi-scale CNN based on region proposals for efficient breast abnormality recognition","volume":"78","author":"Bakkouri","year":"2019","journal-title":"Multimed. Tool. Appl."},{"issue":"29","key":"10.1016\/j.compbiomed.2026.111663_bib15","doi-asserted-by":"crossref","first-page":"20483","DOI":"10.1007\/s11042-019-07988-1","article-title":"Computer-aided diagnosis (CAD) system based on multi-layer feature fusion network for skin lesion recognition in dermoscopy images","volume":"79","author":"Bakkouri","year":"2020","journal-title":"Multimed. Tool. Appl."},{"issue":"4","key":"10.1016\/j.compbiomed.2026.111663_bib16","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1007\/s11760-022-02325-w","article-title":"MLCA2F: Multi-level context attentional feature fusion for COVID-19 lesion segmentation from CT scans","volume":"17","author":"Bakkouri","year":"2023","journal-title":"Signal, Image and Video Processing"},{"issue":"8","key":"10.1016\/j.compbiomed.2026.111663_bib17","doi-asserted-by":"crossref","first-page":"10743","DOI":"10.1007\/s11042-022-12242-2","article-title":"BG-3DM2F: bidirectional gated 3D multi-scale feature fusion for Alzheimer's disease diagnosis","volume":"81","author":"Bakkouri","year":"2022","journal-title":"Multimed. Tool. Appl."},{"key":"10.1016\/j.compbiomed.2026.111663_bib18","first-page":"1","article-title":"Edge-Aware dual-branch CNN Architecture for alzheimer's disease diagnosis","author":"Li","year":"2026","journal-title":"Journal of Imaging Informatics in Medicine"},{"key":"10.1016\/j.compbiomed.2026.111663_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.109070","article-title":"MKP-H2ANet: a lightweight multi-kernel pyramid hybrid adaptive attention convolutional neural network for Alzheimer's disease diagnosis","volume":"113","author":"Cui","year":"2026","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib20","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.109073","article-title":"MANet: a missing-aware attention network for early Alzheimer's disease diagnosis using longitudinal and multimodal data","volume":"113","author":"Liu","year":"2026","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2025.109810","article-title":"Alzheimer Disease detection and classification using optimized neural network","volume":"187","author":"Balakrishnan","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.compbiomed.2026.111663_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2025.108703","article-title":"MCNEL: a multi-scale convolutional network and ensemble learning for Alzheimer's disease diagnosis","volume":"264","author":"Yan","year":"2025","journal-title":"Comput. Methods Progr. Biomed."},{"key":"10.1016\/j.compbiomed.2026.111663_bib23","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105442","article-title":"Pipelined deep learning architecture for the detection of Alzheimer's disease","volume":"87","author":"Prasath","year":"2024","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2022.107291","article-title":"VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer's disease prediction","volume":"229","author":"Hu","year":"2023","journal-title":"Comput. Methods Progr. Biomed."},{"key":"10.1016\/j.compbiomed.2026.111663_bib25","article-title":"AlzFusionFormer: integrating multiple transformers for early Alzheimer's disease detection from multi-modal data","volume":"112","author":"Gu","year":"2026","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib26","article-title":"Regional attention-enhanced vision transformer for accurate Alzheimer's disease classification using sMRI data","volume":"197","author":"Navin","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.compbiomed.2026.111663_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2025.110951","article-title":"ResGSNet: enhanced local attention with Global Scoring Mechanism for the early detection and treatment of Alzheimer's disease","volume":"197","author":"Chen","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.compbiomed.2026.111663_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2026.102722","article-title":"An interpretable machine learning framework with data-informed imaging biomarkers for diagnosis and prediction of Alzheimer's disease","volume":"128","author":"Kang","year":"2026","journal-title":"Comput. Med. Imag. Graph."},{"key":"10.1016\/j.compbiomed.2026.111663_bib29","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2025.108049","article-title":"Multi-relational mixed perception based short time series prediction of Alzheimer's disease progression","volume":"110","author":"Yang","year":"2025","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108564","article-title":"HAMMF: hierarchical attention-based multi-task and multi-modal fusion model for computer-aided diagnosis of Alzheimer's disease","volume":"176","author":"Liu","year":"2024","journal-title":"Comput. Biol. Med."},{"issue":"4","key":"10.1016\/j.compbiomed.2026.111663_bib31","doi-asserted-by":"crossref","first-page":"287","DOI":"10.32628\/IJSRST52310258","article-title":"Prediction of alzhimers disease from 4 class of MRI images using inception V3 model in deep learning","volume":"10","author":"Poornima","year":"2023","journal-title":"International Journal of Scientific Research in Science and Technology"},{"key":"10.1016\/j.compbiomed.2026.111663_bib32","doi-asserted-by":"crossref","first-page":"38287","DOI":"10.1007\/s11042-025-20679-4","article-title":"Detection and classification of mammogram using ResNet-50","volume":"84","author":"Patil","year":"2025","journal-title":"Multimed. Tool. Appl."},{"key":"10.1016\/j.compbiomed.2026.111663_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105189","article-title":"CNN and swin-transformer based efficient model for Alzheimer's disease diagnosis with sMRI","volume":"86","author":"Xin","year":"2023","journal-title":"Biomed. Signal Process Control"},{"key":"10.1016\/j.compbiomed.2026.111663_bib34","doi-asserted-by":"crossref","DOI":"10.1016\/j.artmed.2023.102678","article-title":"Alzheimer's Disease Neuroimaging Initiative. Diagnosis of Alzheimer's disease by joining dual attention CNN and MLP based on structural MRIs, clinical and genetic data","volume":"145","author":"Qiang","year":"2023","journal-title":"Artif. Intell. Med."}],"container-title":["Computers in Biology and Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482526002271?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482526002271?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T20:39:36Z","timestamp":1784666376000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0010482526002271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":34,"alternative-id":["S0010482526002271"],"URL":"https:\/\/doi.org\/10.1016\/j.compbiomed.2026.111663","relation":{},"ISSN":["0010-4825"],"issn-type":[{"value":"0010-4825","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A computational framework for Alzheimer's disease detection using SwinRes Transformer","name":"articletitle","label":"Article Title"},{"value":"Computers in Biology and Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compbiomed.2026.111663","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":"111663"}}