Google Research has published a study examining how an AI-assisted ultrasound system performs across different clinical environments. The system was originally trained on ultrasound data from North Carolina in the United States and Zambia, using commercial probes from Sonosite, GE, and Butterfly Networks. Researchers then paired the model with the Clarius C3 handheld transabdominal probe and ran prospective testing in two very different care settings: a high-resource academic medical center in Chicago and a community clinic network in Nairobi, Kenya.
The study used a small pilot dataset from 120 participants in Chicago, roughly 6% of the original training set, to adapt the model to the new probe hardware and extend gestational age prediction beyond 36 weeks. To test generalizability, the team did not use data from the Nairobi site for fine-tuning, keeping the Kenya validation fully independent. The research also included multiple-gestation pregnancies to assess how the system performs in more complex cases.
Google Research has published a study evaluating the performance of an AI-assisted ultrasound system across varied clinical settings.
The system was originally trained on ultrasound data from North Carolina in the United States and Zambia, using commercial ultrasound probes from Sonosite, GE, and Butterfly Networks. Researchers then paired it with the Clarius C3 handheld transabdominal probe and conducted prospective testing at a high-resource academic medical center in Chicago and a community clinic network in Nairobi, Kenya.
The study used a small pilot dataset from 120 participants in Chicago, about 6% of the original training set, to adjust the model so it could work with the new probe hardware and extend gestational age prediction beyond 36 weeks.
To evaluate generalizability, the researchers did not use data from the Nairobi site for fine-tuning, keeping the clinical validation in Kenya strictly independent. The study also included multiple-gestation pregnancies to assess the system’s overall utility in more complex cases.
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