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Using deep-learning architecture to identify rare, life-threatening disorders from fetal ultrasound scans

Artificial intelligence is poised to play a truly transformative role in global health care. The convergence of medicine and AI might eventually prove to be more impactful than the unraveling of the genome.

Now, in a new proof-of-concept study led by Dr. Mark Walker at the uOttawa Faculty of Medicine, researchers are pioneering the use of a unique AI-based deep learning model as an assistive tool for the rapid and accurate reading of ultrasound images.

It’s trailblazing work because although deep learning models have become increasingly popular in interpreting medical images and detecting disorders, figuring out how its application can work in obstetric ultrasonography is in its nascent stages. Few AI-enabled studies have been published in this field.

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