Raymond P. Najjar, PhD

Affiliations: 
2008-2012 Chronobiology INSERM Bron, France 
 2012-2015 Psychiatry and Behavioral Sciences Stanford University, Palo Alto, CA 
 2015- Visual Neurosciences Singapore Eye Research Institute 
 2022- Ophthalmology National University of Singapore, Singapore, Singapore 
Area:
Visual Neurosciences, Melanopsin, Pupillometry, Myopia, Light, Artificial Intelligence
Website:
https://www.researchgate.net/profile/Raymond_Najjar
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Publications

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Biswas S, El Kareh A, Qureshi M, et al. (2024) The influence of the environment and lifestyle on myopia. Journal of Physiological Anthropology. 43: 7
Lin MY, Najjar RP, Tang Z, et al. (2024) The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs. Journal of Aapos : the Official Publication of the American Association For Pediatric Ophthalmology and Strabismus
Spitschan M, Kervezee L, Lok R, et al. (2023) ENLIGHT: A consensus checklist for reporting laboratory-based studies on the non-visual effects of light in humans. Ebiomedicine. 98: 104889
Biousse V, Najjar RP, Tang Z, et al. (2023) Application of a deep learning system to detect papilledema on nonmydriatic ocular fundus photographs in an emergency department. American Journal of Ophthalmology
Tan RKY, Panda SK, Braeu FA, et al. (2023) The Structural Layers of the Porcine Iris Exhibit Inherently Different Biomechanical Properties. Investigative Ophthalmology & Visual Science. 64: 11
Finkelstein MT, Nongpiur ME, Husain R, et al. (2023) Handheld chromatic pupillometry can reliably detect functional glaucomatous damage in eyes with high myopia. The British Journal of Ophthalmology
Biswas S, Muralidharan AR, Betzler BK, et al. (2023) A Duration-Dependent Interaction Between High-Intensity Light and Unrestricted Vision in the Drive for Myopia Control. Investigative Ophthalmology & Visual Science. 64: 31
Sathianvichitr K, Lamoureux O, Nakada S, et al. (2023) Through the eyes into the brain, using artificial intelligence. Annals of the Academy of Medicine, Singapore. 52: 88-95
Vasseneix C, Nusinovici S, Xu X, et al. (2023) Deep Learning System Outperforms Clinicians in Identifying Optic Disc Abnormalities. Journal of Neuro-Ophthalmology : the Official Journal of the North American Neuro-Ophthalmology Society
Chan E, Tang Z, Najjar RP, et al. (2023) A Deep Learning System for Automated Quality Evaluation of Optic Disc Photographs in Neuro-Ophthalmic Disorders. Diagnostics (Basel, Switzerland). 13
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