Zebra Medical Vision (http://zebra-med.com/) is announcing today the latest algorithm to be included in its growing Deep Learning Imaging Analytics platform. The algorithm, capable of detecting vertebral fractures, is the latest addition to a line of automated tools that were announced in the past year, among them algorithms that automatically detect low bone mineral density, breast cancer, fatty liver, coronary artery calcium, emphysema, and more.

While less than one third of vertebral compression fractures (VCFs) are effectively diagnosed, VCFs are remarkably common, affecting up to one in four postmenopausal women and nearly one in seven men over the age of 65. More than two million osteoporotic fractures occur annually in the US alone, significantly impairing the lives of those affected and their families, and costing the healthcare system nearly $17 billion USD. Detection of VCFs is thus paramount in the effort to decrease osteoporotic fractures – the most morbid of which are hip fractures. Diagnosing VCFs is of critical importance for implementation of both primary therapeutic and secondary preventative interventions.

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