{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T03:01:59Z","timestamp":1773025319124,"version":"3.50.1"},"reference-count":23,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T00:00:00Z","timestamp":1759708800000},"content-version":"vor","delay-in-days":278,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Biomedical Imaging"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>\n                    Various retinal conditions, such as diabetic macular edema (DME) and choroidal neovascularization (CNV), pose significant risks of visual impairment and vision loss. Early detection through automated and accurate and advanced systems can greatly enhance clinical outcomes for patients as well as for medical staff. This study is aimed at developing a deep learning\u2013based model for the early detection of retinal diseases using OCT images. We utilized a publicly available retinal image dataset comprising images with DME, CNV, drusen, and normal cases. The Inception model was trained and validated using various evaluation metrics. Performance metrics, including accuracy, precision, recall, and\n                    <jats:italic>F<\/jats:italic>\n                    1 score, were calculated. The proposed model achieved an accuracy of 94.2%, with precision, recall, and\n                    <jats:italic>F<\/jats:italic>\n                    1 scores exceeding 92% across all classes. Statistical analysis demonstrated the robustness of the model across folds. Our findings highlight the potential of AI\u2010powered systems in improving early detection of retinal conditions, paving the way for integration into clinical workflows. More efforts are needed to utilize it offline by making it available on ophthalmologist mobile devices to facilitate the diagnosis process and provide better service to patients.\n                  <\/jats:p>","DOI":"10.1155\/ijbi\/6154285","type":"journal-article","created":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T08:51:01Z","timestamp":1759740661000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI\u2010Powered Early Detection of Retinal Conditions: A Deep Learning Approach for Diabetic Retinopathy and Beyond"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2470-1317","authenticated-orcid":false,"given":"Ali Basim","family":"Mahdi","sequence":"first","affiliation":[]},{"given":"Zahraa A.","family":"Mousa Al-Ibraheemi","sequence":"additional","affiliation":[]},{"given":"Zahraa Fadhil","family":"Kadhim","sequence":"additional","affiliation":[]},{"given":"Raffef Jabar","family":"Abbrahim","sequence":"additional","affiliation":[]},{"given":"Yaqeen Sameer","family":"Dhayool","sequence":"additional","affiliation":[]},{"given":"Ghasaq Mankhey","family":"Jabbar","sequence":"additional","affiliation":[]},{"given":"Sajjad A.","family":"Mohammed","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,10,6]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.18203\/2394-6040.ijcmph20240301"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.14569\/IJACSA.2024.0150703"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107834"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-023-02702-z"},{"key":"e_1_2_9_5_2","first-page":"3581","article-title":"AI-Driven Diabetic Retinopathy Detection: Advancements In Early Diagnosis","volume":"30","author":"Herald D.","year":"2024","journal-title":"Educational Administration: Theory and Practice"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISCS61804.2024.10581336"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-024-03139-8"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1080\/17434440.2023.2294364"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.3390\/S21206933"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-47194-0"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.30534\/IJATCSE\/2020\/175942020"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI56570.2024.10635242"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.3390\/app12115363"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.3389\/fncom.2019.00044"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-016-0043-6"},{"key":"e_1_2_9_16_2","volume-title":"Deep Learning, vol. 196","author":"Goodfellow I.","year":"2016"},{"key":"e_1_2_9_17_2","volume-title":"Pattern Recognition and Machine Learning vol. 4","author":"Bishop C. 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Metrics for Multi-Class Classification: An Overview 2020 https:\/\/arxiv.org\/abs\/2008.05756."},{"key":"e_1_2_9_22_2","first-page":"343","article-title":"Synteza i aktywno\u015b\u0107 biologiczna nowych analog\u00f3w tiosemikarbazonowych chelator\u00f3w \u017celaza","volume":"7","author":"Serda M.","year":"2013","journal-title":"Uniw. \u015bl\u0105ski"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.55524\/ijircst.2024.12.1.4"}],"container-title":["International Journal of Biomedical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/ijbi\/6154285","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/ijbi\/6154285","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/ijbi\/6154285","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T02:40:00Z","timestamp":1773024000000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/ijbi\/6154285"}},"subtitle":[],"editor":[{"given":"Qian","family":"Tao","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":23,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["10.1155\/ijbi\/6154285"],"URL":"https:\/\/doi.org\/10.1155\/ijbi\/6154285","archive":["Portico"],"relation":{},"ISSN":["1687-4188","1687-4196"],"issn-type":[{"value":"1687-4188","type":"print"},{"value":"1687-4196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"2025-02-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-09-06","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"6154285"}}