Terrestrial health applications of visual assessment technology and machine learning in spaceflight associated neuro-ocular syndrome
Year: 2022
Type: article
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.
Source: npj Microgravity
Institutions: University of Pittsburgh, University of Nevada, Reno, University College Dublin, Rice University, Houston Methodist, The University of Texas MD Anderson Cancer Center, Baylor College of Medicine, University of Iowa Hospitals and Clinics, Weill Cornell Medicine, The University of Texas Medical Branch at Galveston, Texas A&M University
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,170
Award: G9000339037
OpenAlex ID: W4293049017
