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Early prediction of diabetic retinopathy using a multimodal deep learning framework integrating fundus and OCT imaging.

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Title: Early prediction of diabetic retinopathy using a multimodal deep learning framework integrating fundus and OCT imaging.
Authors: Emara AM; Department of Computer Science, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia., Alkhateeb JH; Department of Computer Engineering, College of Engineering and Computer Science, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia., Atteia G; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia., Turani A; Department of Information Systems, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia., Zraqou J; Department of Computer Science, University of Petra, Amman, Jordan., Elsawaf Z; Department of Pathology, Medical Faculty, Taibah University, Madinah, Saudi Arabia., Jameel A; Department of Computer Science, Faculty of Computing, International Islamic University Islamabad, Islamabad, Pakistan.
Source: Frontiers in medicine [Front Med (Lausanne)] 2026 Jan 09; Vol. 12, pp. 1741146. Date of Electronic Publication: 2026 Jan 09 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Early prediction of diabetic retinopathy using a multimodal deep learning framework integrating fundus and OCT imaging.
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  Data: <searchLink fieldCode="AU" term="%22Emara+AM%22">Emara AM</searchLink>; Department of Computer Science, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Alkhateeb+JH%22">Alkhateeb JH</searchLink>; Department of Computer Engineering, College of Engineering and Computer Science, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Atteia+G%22">Atteia G</searchLink>; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Turani+A%22">Turani A</searchLink>; Department of Information Systems, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Zraqou+J%22">Zraqou J</searchLink>; Department of Computer Science, University of Petra, Amman, Jordan.<br /><searchLink fieldCode="AU" term="%22Elsawaf+Z%22">Elsawaf Z</searchLink>; Department of Pathology, Medical Faculty, Taibah University, Madinah, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Jameel+A%22">Jameel A</searchLink>; Department of Computer Science, Faculty of Computing, International Islamic University Islamabad, Islamabad, Pakistan.
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  Data: <searchLink fieldCode="JN" term="%22101648047%22">Frontiers in medicine</searchLink> [Front Med (Lausanne)] 2026 Jan 09; Vol. 12, pp. 1741146. <i>Date of Electronic Publication: </i>2026 Jan 09 (<i>Print Publication: </i>2025).
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        Value: 10.3389/fmed.2025.1741146
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      – TitleFull: Early prediction of diabetic retinopathy using a multimodal deep learning framework integrating fundus and OCT imaging.
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              Text: 2026 Jan 09
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