ISBN: 9786630562743 - ai and image processing for medical decision support: early detection of keratoconus (4 resultados)

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 92 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The objectives of the research presented in this book focused on exploring artificial intelligence in conjunction with image processing to aid in decision-making for the early detection of keratoconus. First, we highlight the contribution of machine learning techniques to medical image analysis, demonstrating their relevance and effectiveness for the early screening of keratoconus, a progressive corneal disease that requires reliable and early detection. Next, we show that deep learning approaches, particularly those based on convolutional neural networks, offer superior performance for the automated classification of medical images, while also enabling the generation of synthetic images to enrich databases and improve model robustness. Taken together, these contributions highlight the considerable potential of artificial intelligence methods to enhance diagnostic accuracy, optimize the interpretation of medical images, and effectively support clinical decision-making. …

Taschenbuch. Condición: Neu. AI and Image Processing for Medical Decision Support | Early Detection of Keratoconus | Imen Fourati Kallel (u. a.) | Taschenbuch | Englisch | 2026 | Our Knowledge Publishing | EAN 9786630562743 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The objectives of the research presented in this book focused on exploring artificial intelligence in conjunction with image processing to aid in decision-making for the early detection of keratoconus. First, we highlight the contribution of machine learning techniques to medical image analysis, demonstrating their relevance and effectiveness for the early screening of keratoconus, a progressive corneal disease that requires reliable and early detection. Next, we show that deep learning approaches, particularly those based on convolutional neural networks, offer superior performance for the automated classification of medical images, while also enabling the generation of synthetic images to enrich databases and improve model robustness. Taken together, these contributions highlight the considerable potential of artificial intelligence methods to enhance diagnostic accuracy, optimize the interpretation of medical images, and effectively support clinical decision-making. 92 pp. Englisch. …