Artificial intelligence in medicine


Imagine a world in which your health can be constantly monitored with a device that you could purchase.Artificial intelligence is already making strides in detecting undiagnosed disease. In December of last year, a team of researchers at Google trained a deep neural network to detect diabetic retinopathy with higher accuracy than an ophthalmologist.
A growing body of research on AI and medicine underscores its transformative potential. For example, in a study published in August 2017 in Radiology, researchers used more than 1,000 deidentified patient X-rays to train a deep-learning network to detect tuberculosis. The network had close to a 100% accuracy rate, which could be especially promising in areas with shortages of radiologists, according to researchers. Another study, published in April 2017 in PLOS ONE, found that machine-learning algorithms improved the accuracy of cardiovascular risk prediction.
Today, about 7,000 clinicians from 500 institutions worldwide are using and building a diagnostic and management tool that uses AI to glean useful information from the world’s collective medical knowledge.


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