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Generative Pre-Trained Transformers (GPT) and Space Health: A Potential Frontier in Astronaut Health During Exploration Missions

Published online by Cambridge University Press:  02 June 2023

Ethan Waisberg*
Affiliation:
University College Dublin School of Medicine, Belfield, Dublin, Ireland
Joshua Ong
Affiliation:
Michigan Medicine, University of Michigan, Ann Arbor, Michigan USA
Mouayad Masalkhi
Affiliation:
University College Dublin School of Medicine, Belfield, Dublin, Ireland
Nasif Zaman
Affiliation:
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada - Reno, Reno, Nevada USA
Sharif Amit Kamran
Affiliation:
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada - Reno, Reno, Nevada USA
Prithul Sarker
Affiliation:
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada - Reno, Reno, Nevada USA
Andrew G. Lee
Affiliation:
Center for Space Medicine, Baylor College of Medicine, Houston, Texas USA Department of Ophthalmology, Blanton Eye Institute, Houston Methodist Hospital, Houston, Texas USA The Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas USA Departments of Ophthalmology, Neurology, and Neurosurgery, Weill Cornell Medicine, New York, New York USA Department of Ophthalmology, University of Texas Medical Branch, Galveston, Texas USA University of Texas MD Anderson Cancer Center, Houston, Texas USA Texas A&M College of Medicine, Bryan, Texas USA Department of Ophthalmology, The University of Iowa Hospitals and Clinics, Iowa City, Iowa USA
Alireza Tavakkoli
Affiliation:
Human-Machine Perception Laboratory, Department of Computer Science and Engineering, University of Nevada - Reno, Reno, Nevada USA
*
Correspondence: Ethan Waisberg University College Dublin School of Medicine Belfield, Dublin 4, Ireland E-mail: ethan.waisberg@ucdconnect.ie
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Abstract

In anticipation of space exploration where astronauts are traveling away from Earth, and for longer durations with an increasing communication lag, artificial intelligence (AI) frameworks such as large language learning models (LLMs) that can be trained on Earth can provide real-time answers. This emerging technology may be helpful for acute medical emergencies, particularly in austere and distant space environments. In this manuscript, we provide an overview of generative pre-trained transformer (GPT) technology, a rapidly emerging AI technology, and implications, considerations, and limitations of such technology for space health.

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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the World Association for Disaster and Emergency Medicine
Figure 0

Figure 1. ChatGPT-Generated Response from the Prompt: “Help. A Piece of Glass was Floating and Unexpectedly Went Into an Astronaut’s Eye.”Abbreviation: GPT, generative pre-trained transformer.

Figure 1

Figure 2. ChatGPT-Generated Response from the Prompt: “We Don’t Have Any Sterile Saline, Are There Any Alternatives?”Abbreviation: GPT, generative pre-trained transformer.

Figure 2

Figure 3. ChatGPT-Generated Response from the Prompt: “What Antibiotics Should I Use?”Abbreviation: GPT, generative pre-trained transformer.

Figure 3

Figure 4. ChatGPT-Generated Response from the Prompt: “How Frequently Should I Follow-Up Once the Astronaut That Had Glass in His Eye is Stabilized?”Abbreviation: GPT, generative pre-trained transformer.