The algorithm can be 'trained' to recognise patterns and interpret the images helping to detect lung cancers from Ct scans, to diagnose diseases of the eye in people with diabetes and to find the cancer on a microscope slides.
In this case, the artificial intelligence of Google applied to screening of breast cancer has reduced the false positive rate of 5.7% (on cases, Usa) and 1.2% (on cases Gb), and false-negative rates of 9.4% (Usa) and 2.7% (Gb). The diversity of the results is related to the fact that in the United States, mammograms are read by a single radiologist, and the examination is carried out every 1-2 years, while in the United Kingdom, every mammogram is examined by two radiologists, with a third party expert consulted in case of discordant opinions - and the test is done every 3 years. In a separate survey, the system based on The is compared with six radiologists, demonstrating a greater accuracy in the diagnosis.
"Many radiologists do make mistakes, some well outside of the acceptable margins of normal human error," he told the New York Times Constance Lehman of the Massachusetts General Hospital in Boston, is not involved in the study.
In this case the reading of the mammography on the part of the neural systems have proven to be of help. "We have taken the mammograms, we have shown to the radiologists, and we asked to check for the presence or absence of the tumor. Then we submitted to artificial intelligence, and we performed the same test," he explained Mozziyar Etemadi at Northwestern University. The Ai was found to be more accurate radiolog, because unlike humans the computer does not get tired and does not distract you towards the end of a long day of reading of mammograms, has clarified Etemadi.
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