A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps

Author:

Al-Timemy Ali H.12,Mosa Zahraa M.3,Alyasseri Zaid45,Lavric Alexandru6,Lui Marcelo M.7,Hazarbassanov Rossen M.78,Yousefi Siamak910

Affiliation:

1. Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq

2. Centre for Robotics and Neural Systems, Cognitive Institute, School of Engineering, Computing and Mathematics, Plymouth University, Plymouth, UK

3. College of Pharmacy, Uruk University, Baghdad, Iraq

4. Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia

5. ECE Department–Faculty of Engineering, University of Kufa, Najaf, Iraq

6. Computers, Electronics and Automation Department, Stefan cel Mare University of Suceava, Suceava, Bukovina, Romania

7. Hospital de Olhos–CRO, Guarulhos, São Paulo, São Paulo, Brazil

8. Department of Ophthalmology and Visual Sciences, Paulista Medical School, Federal University of São Paulo, São Paulo, Brazil

9. Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, TN, USA

10. Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Subject

Ophthalmology,Biomedical Engineering

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