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NVIDIA Inception startups are deploying AI models trained on massive ultrasound datasets to automate image capture and standardize breast cancer screening, directly addressing the radiologist shortage. This approach reduces scan time from 45 minutes to two while improving sensitivity over traditional 2D methods by eliminating operator variability. The integration of imaging with genomic data aims to create comprehensive patient profiles for better clinical decision-making.

Sources coveringQuantum Zeitgeist, SiliconANGLE

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NVIDIA Inception startups tackle gaps in breast cancer care

Quantum ZeitgeistOctober 6, 20266 min read

Companies in the NVIDIA Inception program are using AI to improve breast cancer care, from 40 million annual mammograms to faster treatment decisions.

Approximately two minutes per breast is now required for a standardized scan using iSono Health’s FDA-cleared ATUSA platform, a significant reduction from the up to 45 minutes needed with conventional handheld ultrasound. The company is one of several in the NVIDIA Inception program applying artificial intelligence to address widening gaps in breast cancer care, a field where 40 million mammograms are performed annually in the U.S. amid a projected shortfall of tens of thousands of radiologists. “Getting the scan closer to the patient is the first breakthrough,” said Neda Razavi, CEO of iSono Health, envisioning increasingly informative scans to aid clinical decision-making. This accelerated acquisition is enabled by artificial intelligence trained on over 1.5 million ultrasound frames, automating image capture with NVIDIA…

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