Artificial Intelligence Applications in Space Medicine

被引:1
作者
Cheung, Hoi Ching [1 ]
De Louche, Calvin [2 ]
Komorowski, Matthieu [3 ]
机构
[1] Imperial Coll London, Fac Med, Exhibition Rd, London SW7 2AZ, England
[2] Univ Southampton, Fac Med, Southampton, England
[3] Imperial Coll London, Consultant Anesthesiol & Crit Care, Div Anaesthet Pain Med & Intens Care, Fac Med,Dept Surg & Canc, London, England
关键词
space medicine; space exploration; artificial intelligence; machine learning; decision support; SPACEFLIGHT; SYSTEM; MICROGRAVITY; FEASIBILITY; ULTRASOUND; ALGORITHM; PRESSURE; SURGERY; FLIGHT; BLOOD;
D O I
10.3357/AMHP.6178.2023
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
INTRODUCTION: During future interplanetary space missions, a number of health conditions may arise, owing to the hostile environment of space and the myriad of stressors experienced by the crew. When managing these conditions, crews will be required to make accurate, timely clinical decisions at a high level of autonomy, as telecommunication delays and increasing distances restrict real-time support from the ground. On Earth, artificial intelligence (Ai) has proven successful in healthcare, augmenting expert clinical decision-making or enhancing medical knowledge where it is lacking. Similarly, deploying Ai tools in the context of a space mission could improve crew self-reliance and healthcare delivery.METHODS: We conducted a narrative review to discuss existing Ai applications that could improve the prevention, recognition, evaluation, and management of the most mission-critical conditions, including psychological and mental health, acute radiation sickness, surgical emergencies, spaceflight-associated neuro-ocular syndrome, infections, and cardiovascular deconditioning.RESULTS: Some examples of the applications we identified include Ai chatbots designed to prevent and mitigate psychological and mental health conditions, automated medical imaging analysis, and closed-loop systems for hemodynamic optimization. We also discuss at length gaps in current technologies, as well as the key challenges and limitations of developing and deploying Ai for space medicine to inform future research and innovation. indeed, shifts in patient cohorts, space-induced physiological changes, limited size and breadth of space biomedical datasets, and changes in disease characteristics may render the models invalid when transferred from ground settings into space.
引用
收藏
页码:610 / 622
页数:13
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