This book details the development of a deep learning model to automate the detection of diabetic maculopathy (DM), a leading cause of vision loss. Traditionally, diagnosing DM from retinal images is a time-consuming manual process. Using a MobileNet model trained on the Asia Pacific Tele-Ophthalmology Society (APTOS) dataset from Kaggle, the system can classify fundus images into different stages of DM severity. The significant step toward using AI for the automated diagnosis of diabetic eye diseases, with focus on testing the model in real-world clinical settings and adding explainability to its predictions to increase trust and understanding. This advancement highlights the growing role of deep learning in improving healthcare outcomes for diabetic patients.
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Paperback. Condition: new. Paperback. This book details the development of a deep learning model to automate the detection of diabetic maculopathy (DM), a leading cause of vision loss. Traditionally, diagnosing DM from retinal images is a time-consuming manual process. Using a MobileNet model trained on the Asia Pacific Tele-Ophthalmology Society (APTOS) dataset from Kaggle, the system can classify fundus images into different stages of DM severity. The significant step toward using AI for the automated diagnosis of diabetic eye diseases, with focus on testing the model in real-world clinical settings and adding explainability to its predictions to increase trust and understanding. This advancement highlights the growing role of deep learning in improving healthcare outcomes for diabetic patients. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786209044632
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book details the development of a deep learning model to automate the detection of diabetic maculopathy (DM), a leading cause of vision loss. Traditionally, diagnosing DM from retinal images is a time-consuming manual process. Using a MobileNet model trained on the Asia Pacific Tele-Ophthalmology Society (APTOS) dataset from Kaggle, the system can classify fundus images into different stages of DM severity. The significant step toward using AI for the automated diagnosis of diabetic eye diseases, with focus on testing the model in real-world clinical settings and adding explainability to its predictions to increase trust and understanding. This advancement highlights the growing role of deep learning in improving healthcare outcomes for diabetic patients.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. Seller Inventory # 9786209044632
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Taschenbuch. Condition: Neu. Automated Macular Health Screening via Deep Learning | AI for Macular Health | Neelapala Anil Kumar | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209044632 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Seller Inventory # 134197474