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A bidirectional cross-modal attention mechanism enhances associations between imaging and clinical modalities, followed by an adaptive gated fusion module that dynamically integrates concatenated global multimodal features with cross-modal interaction features. To evaluate the robustness of the proposed framework, all experiments were repeated using five different random seeds, and the results are reported as mean \u00b1 standard deviation. Experimental results demonstrate competitive performance across multiple classification tasks, achieving accuracies of 95.67% \u00b1 1.70% for three-class classification (CN vs MCI vs AD) and 93.64% \u00b1 2.36% for four-class classification (CN vs early MCI (EMCI) vs late MCI (LMCI) vs AD). For binary classification (AD vs CN, AD vs MCI, MCI vs CN, and EMCI vs LMCI), the method achieves accuracies of 96.83% \u00b1 1.53%, 95.33% \u00b1 1.00%, 95.83% \u00b1 1.39%, and 93.61% \u00b1 2.35%, respectively. The proposed framework provides an effective solution for multimodal DL-based computer-aided diagnosis of AD.<\/jats:p>","DOI":"10.1088\/2057-1976\/ae995e","type":"journal-article","created":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T22:47:56Z","timestamp":1786661276000},"page":"045067","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Bidirectional cross-modal attention with adaptive gating for multimodal Alzheimer\u2019s disease classification"],"prefix":"10.1088","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5341-2491","authenticated-orcid":true,"given":"Xiaoli","family":"Yang","sequence":"first","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1269-2311","authenticated-orcid":true,"given":"Chenchen","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Li","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0200-7509","authenticated-orcid":true,"given":"Angchao","family":"Duan","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiayi","family":"Zhou","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6054-7872","authenticated-orcid":true,"given":"Jiawen","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7892-0178","authenticated-orcid":true,"given":"Yuanbo","family":"Chen","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"bpexae995ebib1","doi-asserted-by":"publisher","first-page":"5097","DOI":"10.3390\/s20185097","type":"journal-article","article-title":"3D deep learning on medical images: a review","volume":"20","author":"Singh","year":"2020","journal-title":"Sensors"},{"key":"bpexae995ebib2","doi-asserted-by":"publisher","first-page":"220","DOI":"10.3389\/fnagi.2019.00220","type":"journal-article","article-title":"Deep learning in Alzheimer\u2019s disease: diagnostic classification and prognostic prediction using neuroimaging data","volume":"11","author":"Jo","year":"2019","journal-title":"Front. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-05-20","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-08-13","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-08-25","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}