Optimizing autonomous artificial intelligence diagnostics for neuro-ocular health in space missions

Area of Science:

• Space medicine
• Artificial intelligence in healthcare
• Ophthalmology

Background:

• Spaceflight-Associated Neuro-Ocular Syndrome (SANS) poses a significant risk to astronaut vision during long-duration space missions.
• Current SANS monitoring relies on pre- and post-flight examinations, lacking in-flight diagnostic capabilities.
• There is a critical need for autonomous, real-time health monitoring tools for astronauts.

Purpose of the Study:

• To explore the potential of AI, specifically xAI's Grok platform, as an in-flight diagnostic tool for SANS.
• To investigate adapting Grok's high-resolution imaging for early SANS indicator detection.
• To propose a pathway for autonomous SANS management in space.

Main Methods:

• Conceptual adaptation of Grok's AI platform for space-based health monitoring.
• Identifying potential SANS indicators detectable by high-resolution imaging (e.g., optic nerve edema, globe morphology changes).
• Highlighting the need for algorithmic and hardware modifications for spaceflight conditions.

Main Results:

• Grok's imaging capabilities show potential for detecting early SANS indicators.
• Adaptation requires addressing microgravity-induced physiological shifts.
• Autonomous SANS management is feasible with advanced AI diagnostics.

Conclusions:

• AI platforms like Grok can be repurposed for critical space health monitoring.
• Real-time SANS diagnostics are essential for astronaut safety on extended missions, including Mars.
• Advancing AI diagnostics supports autonomous health management in isolated environments.