Deep learning in ophthalmic and orbital ultrasound for spaceflight associated neuro-ocular syndrome (SANS)
Author:
Publisher
Springer Science and Business Media LLC
Subject
Ophthalmology
Link
https://www.nature.com/articles/s41433-023-02877-2.pdf
Reference5 articles.
1. Feng L, Zhang Y, Wei W, Qiu H, Shi M. Applying deep learning to recognize the properties of vitreous opacity in ophthalmic ultrasound images. Eye. 2023;37:1–6.
2. Ong J, Waisberg E, Masalkhi M, Kamran SA, Lowry K, Sarker P, et al. Artificial intelligence frameworks to detect and investigate the pathophysiology of spaceflight associated neuro-ocular syndrome (SANS). Brain Sci. 2023;13:1148.
3. Ong J, Tavakkoli A, Zaman N, Kamran SA, Waisberg E, Gautam N, et al. Terrestrial health applications of visual assessment technology and machine learning in spaceflight associated neuro-ocular syndrome. Npj Microgravity. 2022;8:1–12.
4. Waisberg E, Ong J, Kamran SA, Paladugu P, Zaman N, Lee AG, et al. Transfer learning as an AI-based solution to address limited datasets in space medicine. Life Sci Space Res. 2023;36:36–8.
5. Dinatolo MF, Cohen LY. Monitoring the Impact of Spaceflight on the Human Brain. Life. 2022;12:1060.
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1. Near infrared/ red light therapy a potential countermeasure for mitochondrial dysfunction in spaceflight associated neuro-ocular syndrome (SANS);Eye;2024-05-03
2. Mitochondrial dysfunction in Spaceflight Associated Neuro-Ocular Syndrome (SANS): a molecular hypothesis in pathogenesis;Eye;2024-02-07
3. Addressing Empty Space Myopia to Enable Deep Space Travel with Extended Reality Auditory Biofeedback;International Journal of Aviation, Aeronautics, and Aerospace;2024-01-01
4. Response to ‘Deep learning in ophthalmic ultrasound to enable further insights in Spaceflight Associated Neuro-Ocular Syndrome (SANS)’;Eye;2023-12-22
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