Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model.

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Bibliographic Details
Title: Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model.
Authors: Shoaib MR; School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore., Emara HM; Department of Electronics and Electrical Communications Engineering, Ministry of Higher Education Pyramids Higher Institute (PHI) for Engineering and Technology, 6th of October, 12566, Egypt., Zhao J; School of Computer Science and Engineering, Nanyang Technological University, Singapore, 639798, Singapore. Electronic address: junzhao@ntu.edu.sg., El-Shafai W; Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh, 11586, Saudi Arabia; Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt., Soliman NF; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia., Mubarak AS; Electrical Engineering Department, Aswan Faculty of Engineering, Aswan University, Aswan, 81542, Egypt., Omer OA; Electrical Engineering Department, Aswan Faculty of Engineering, Aswan University, Aswan, 81542, Egypt., El-Samie FEA; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia., Esmaiel H; Electrical Engineering Department, Aswan Faculty of Engineering, Aswan University, Aswan, 81542, Egypt.
Source: Computers in biology and medicine [Comput Biol Med] 2024 Feb; Vol. 169, pp. 107834. Date of Electronic Publication: 2023 Dec 11.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-0534
DOI:10.1016/j.compbiomed.2023.107834