Artificial Intelligence According to data from the Spanish Association Against Cancer, breast cancer is the most common malignant tumor among women worldwide. It is estimated that one in eight women will suffer throughout his life and, although it is the leading cause of death from cancer among women, his death rate in Spain is the lowest. Patient survival is on the rise thanks to therapies and advances in the disease, as well as improvements in its early detection. Something that could revolutionary influence a Google device.
It is an Artificial Intelligence capable of analyzing more efficiently than experts the diagnostic tests of breast cancer. At least, this was determined by a study published in the journal Nature, and it is that mammography detection can be complicated if the cancer is hidden by breast tissue. According to the American Cancer Society, mammograms do not detect about one in five breast cancers and more than half of women are diagnosed with a false positive every 10 years. That is why, through AI, it is proven to make more efficient observations.
Mammograms of 25,856 women from the United Kingdom and 3,097 from the United States were used for the study. The Google tool had to identify the presence of malignant tumors on the mammograms of women who had been diagnosed by biopsies and other more conclusive tests.
The Google Health team, led by scientist Scott Mayer McKinney, in collaboration with the Cancer Research UK Imperial Center, the University of Northwestern Illinois, and the Royal Surrey County Hospital assure in their study that Google’s system surpassed all human readers and recorded a total reduction of 3.5% in false positives and 8.1% in false negatives.
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Although, yes, to make more precise evaluations of this technology, they warn that it is necessary to carry out clinical trials because, according to the study, “the real world is more complicated and diverse than the controlled research environment of this study.”
Even so, at this point, the data yielded is very encouraging and, with pending clinical trials, the study sees “promising signs that this device could increase the accuracy and efficiency of screening programs and reduce waiting times, as well. like the stress of the patients. “