This very cool NASA and Google collaboration is an example of the later. That’s their mission – to preserve astronaut health during long-duration space exploration. The two logics recently launched the creation of a proof-of-concept AI medical assistant, named CMO-DA. This creative assistant is powered by Google’s Vertex AI platform. This new effort comes at a time when human spaceflight missions are increasingly getting longer and flying farther from our planet. These long travels create immense difficulties in protecting the crew’s health.
Read more about this monumental breakthrough here from TechCrunch’s Aria Alamalhodaei, who covered this remarkable technological leap. Alamalhodaei, based in Austin, Texas, has reported on the commercial space and defense industries. He provides colorful lessons and practical tips from the cutting edge of these fast-moving future fields. She also received a Master’s degree in art history from the illustrious Courtauld Institute of Art in London. This incredible accomplishment is a great testament to her varied academic journey.
The AI medical assistant has been tested through three different medical scenarios: an ankle injury, flank pain, and ear pain. Those results showed an excitingly high diagnostic accuracy overall. The flank pain evaluation showed a 74% chance of being right. The ear pain assessment aced the assessment with 80% accuracy. The greatest accuracy of 88% was reached for the ankle injury. These findings suggest that the AI could serve as a critical tool in real-time medical assessments for astronauts in space.
CMO-DA takes a multimodal approach — drawing on speech, text, and images. All of this amazing capability runs inside of Google Cloud’s Vertex AI environment. This flexibility gives the AI the power to take in symptoms and return an easy-to-understand treatment suggestion in no time.
As NASA and Google work to refine this technology, specialists say its consequences reach far past astronaut travel. David Cruley remarked on the potential broader applications of the tool, stating, “the lessons learned from this tool could have applicability to other areas of health.”
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