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MDL-CA: a multimodal deep learning approach with a cross attention mechanism for accurate brain cancer diagnosis.

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Title: MDL-CA: a multimodal deep learning approach with a cross attention mechanism for accurate brain cancer diagnosis.
Authors: Sarwar S; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan., Majeed S; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan., Nawaz A; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan., Bibi R; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan., Lee SW; Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.; Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea.; Department of MetaBioHealth, Sungkyunkwan University, Suwon, Republic of Korea.; Personalized Cancer Immunotherapy Research Center, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.; Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Source: Frontiers in public health [Front Public Health] 2026 Jan 05; Vol. 13, pp. 1687335. Date of Electronic Publication: 2026 Jan 05 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Editorial Office Country of Publication: Switzerland NLM ID: 101616579 Publication Model: eCollection Cited Medium: Internet ISSN: 2296-2565 (Electronic) Linking ISSN: 22962565 NLM ISO Abbreviation: Front Public Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Sarwar+S%22">Sarwar S</searchLink>; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan.<br /><searchLink fieldCode="AU" term="%22Majeed+S%22">Majeed S</searchLink>; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan.<br /><searchLink fieldCode="AU" term="%22Nawaz+A%22">Nawaz A</searchLink>; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan.<br /><searchLink fieldCode="AU" term="%22Bibi+R%22">Bibi R</searchLink>; University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi, Rawalpindi, Pakistan.<br /><searchLink fieldCode="AU" term="%22Lee+SW%22">Lee SW</searchLink>; Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.; Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea.; Department of MetaBioHealth, Sungkyunkwan University, Suwon, Republic of Korea.; Personalized Cancer Immunotherapy Research Center, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea.; Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
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  Data: <searchLink fieldCode="JN" term="%22101616579%22">Frontiers in public health</searchLink> [Front Public Health] 2026 Jan 05; Vol. 13, pp. 1687335. <i>Date of Electronic Publication: </i>2026 Jan 05 (<i>Print Publication: </i>2025).
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        Value: 10.3389/fpubh.2025.1687335
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              Text: 2026 Jan 05
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