Computers were as good or better than doctors at detecting tiny lung cancers on CT scans, in a study by researchers from Google and several medical centers.
The technology is a work in progress, not ready for widespread use, but the new report, published Monday in the journal Nature Medicine, offers a glimpse of the future of artificial intelligence in medicine.
One of the most promising areas is recognizing patterns and interpreting images — the same skills that humans use to read microscope slides, X-rays, M.R.I.s and other medical scans.
By feeding huge amounts of data from medical imaging into systems called artificial neural networks, researchers can train computers to recognize patterns linked to a specific condition, like pneumonia, cancer or a wrist fracture that would be hard for a person to see. The system follows an algorithm, or set of instructions, and learns as it goes. The more data it receives, the better it becomes at interpretation.
The process, known as deep learning, is already being used in many applications, like enabling computers to understand speech and identify objects so that a self-driving car will recognize a stop sign and distinguish a pedestrian from a telephone pole. In medicine, Google has already created systems to help pathologists read microscope slides to diagnose cancer, and to help ophthalmologists detect eye disease in people with diabetes.
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https://www.nytimes.com/2019/05/20/health/cancer-artificial-intelligence-ct-scans.html
