{"id":8003,"date":"2018-01-19T07:00:30","date_gmt":"2018-01-19T15:00:30","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=8003"},"modified":"2017-12-02T21:37:08","modified_gmt":"2017-12-03T05:37:08","slug":"deep-learning-and-artificial-intelligence-algorithms-will-change-how-health-care-is-delivered","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/deep-learning-and-artificial-intelligence-algorithms-will-change-how-health-care-is-delivered\/","title":{"rendered":"Deep Learning and Artificial Intelligence: Algorithms Will Change How Health Care is Delivered"},"content":{"rendered":"<p>Machines are beginning to outperform humans at highly-specific tasks that often take humans years to master.\u00a0 A Deep Learning <a href=\"https:\/\/stanfordmlgroup.github.io\/projects\/chexnet\/\">algorithm at Stanford<\/a>, for example, recently was trained to be able to detect pneumonia from x-rays of patients, and the accuracy of the machine predictions exceeded that of four trained radiologists.<\/p>\n<p>The algorithm was trained on 100,000 x-ray images released from the National Institutes of Health. In addition to pneumonia, the algorithm also was able to more accurately identify from x-rays 14 additional diseases which include fibrosis, hernias, and cell masses.<\/p>\n<p><a href=\"https:\/\/rajpurkar.github.io\/\">Pranav Rajpurkar<\/a>, a graduate student in the Stanford Machine Learning Group,<a href=\"https:\/\/news.stanford.edu\/2017\/11\/15\/algorithm-outperforms-radiologists-diagnosing-pneumonia\/\"> said that<\/a> &#8220;interpreting X-ray images to diagnose pathologies like pneumonia is very challenging, and we know that there\u2019s a lot of variability in the diagnoses radiologists arrive at.&#8221;<\/p>\n<p><a href=\"http:\/\/www.andrewng.org\/\">Andrew Ng<\/a>, former chief scientist at Chinese tech company Baidu,<a href=\"https:\/\/www.technologyreview.com\/s\/608234\/the-machines-are-getting-ready-to-play-doctor\/\"> said that<\/a> &#8220;I&#8217;ve been encouraged by how quickly people are accepting the idea that deep learning can diagnose at an accuracy superior to doctors in select verticals. We still have work ahead to get these algorithms into the health-care system&#8217;s workflow. 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