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Google AI Tool Bests Clinicians in Breast Cancer Detection Study
January 3, 2020
A Google artificial intelligence tool may predict breast cancer better than doctors, according to a study published Wednesday in the journal Nature.
The algorithm, which was trained on almost 91,000 mammogram scans from women in the U.S. and U.K., resulted in almost 6% fewer incorrect cancer diagnoses and 9% fewer false negatives than standard clinical practice when used in the U.S. In the U.K. those figures were 1% and 3% respectively.
Yet the evidence for AI’s value-add in diagnostics is still shaky. Developers of such algorithms stress they should be used as tools on top of a clinician’s judgment, not a stand-alone diagnostic in place of it.
Roughly one in eight women in the U.S. will develop invasive breast cancer over the course of her lifetime, according to the American Cancer Society. Early detection of abnormal tissue or tumor is critically important for treatment, but mammograms have their limitations.
Clinicians fail to catch about a fifth of all breast cancer cases, and half of U.S. women receiving annual mammograms in a given decade will be incorrectly told they have breast cancer when they actually don’t, the cancer group says.
Google Health’s new tool, developed in tandem with its British subsidiary DeepMind, Northwestern Medicine and Imperial College London and the University of Cambridge, improved mistakes in both areas. False positives were reduced by 5.7% and 1.2%, and false negatives were reduced by 9.4% and 2.7% in the U.S. and U.K., respectively.
Written by: Rebecca Pifer
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