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Terrestrial health applications of visual assessment technology and machine learning in spaceflight associated neuro-ocular syndrome

NPJ microgravity, 2022-08, Vol.8 (1), p.37-37, Article 37 [Peer Reviewed Journal]

The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2373-8065 ;EISSN: 2373-8065 ;DOI: 10.1038/s41526-022-00222-7 ;PMID: 36008494

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  • Title:
    Terrestrial health applications of visual assessment technology and machine learning in spaceflight associated neuro-ocular syndrome
  • Author: Ong, Joshua ; Tavakkoli, Alireza ; Zaman, Nasif ; Kamran, Sharif Amit ; Waisberg, Ethan ; Gautam, Nikhil ; Lee, Andrew G
  • Subjects: Aerospace medicine ; Astronauts ; Computer science ; Cooperation ; Edema ; Hypotheses ; Intracranial pressure ; Learning algorithms ; Machine learning ; Medicine ; Moon ; Ophthalmology ; Optic nerve ; Pathogenesis ; Pathophysiology ; Space exploration ; Space flight ; Translation ; Virtual reality ; Visual discrimination learning ; Visual impairment
  • Is Part Of: NPJ microgravity, 2022-08, Vol.8 (1), p.37-37, Article 37
  • Description: Abstract The neuro-ocular effects of long-duration spaceflight have been termed Spaceflight Associated Neuro-Ocular Syndrome (SANS) and are a potential challenge for future, human space exploration. The underlying pathogenesis of SANS remains ill-defined, but several emerging translational applications of terrestrial head-mounted, visual assessment technology and machine learning frameworks are being studied for potential use in SANS. To develop such technology requires close consideration of the spaceflight environment which is limited in medical resources and imaging modalities. This austere environment necessitates the utilization of low mass, low footprint technology to build a visual assessment system that is comprehensive, accessible, and efficient. In this paper, we discuss the unique considerations for developing this technology for SANS and translational applications on Earth. Several key limitations observed in the austere spaceflight environment share similarities to barriers to care for underserved areas on Earth. We discuss common terrestrial ophthalmic diseases and how machine learning and visual assessment technology for SANS can help increase screening for early intervention. The foundational developments with this novel system may help protect the visual health of both astronauts and individuals on Earth.
  • Publisher: New York: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 2373-8065
    EISSN: 2373-8065
    DOI: 10.1038/s41526-022-00222-7
    PMID: 36008494
  • Source: AUTh Library subscriptions: ProQuest Central
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