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.

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The human body undergoes many changes during long-duration spaceflight including musculoskeletal, visual, and behavioral changes. Several of these microgravity-induced effects serve as potential barriers to future exploration missions. The advent of artificial intelligence (AI) in medicine has progressed rapidly and has many promising applications for maintaining and monitoring astronaut health during spaceflight. However, the austere environment and unique nature of spaceflight present with challenges in successfully training and deploying successful systems for upholding astronaut health and mission performance. In this article, the dynamic barriers facing AI development in space medicine are explored. These diverse challenges range from limited astronaut data for algorithm training to ethical/legal considerations in deploying automated diagnostic systems in the setting of the medically limited space environment. How to address these challenges is then discussed and future directions for this emerging field of research.

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