Money is pouring in to chatbots - instant messaging tools that allow customers to communicate with AI software. Home Depot, Lowe's, H&M, and most large banks are turning to AI to automate customer service. Retailers and banks are actually the biggest spenders. The entire healthcare industry will have spent more than $1 billion on AI in 2017, according to IDC.Īnd they're not alone. Today, doctors use CAD to help them identify a variety of diseases including Alzheimer's, heart defects, diabetic complications, and a whole range of cancers.
It can identify skin cancer - an annual killer of 10,000 - as well as dermatologists can.
student last year trained a neural network to recognize thousands of different skin diseases. Using a data set of skin lesion images some 100 times larger than prior ones, a Stanford Ph.D. What's different now is that huge data sets and enormous processing power are combining with deep learning to perfect object recognition. The computer could spit out likelihoods for over a dozen different conditions that the patient might have. 12 meant that you noticed some stuff in the lung that's not supposed to be there. Doctors could enter "True" or "False" for 21 inputs. One 1990 paper diagrams a neural network for identifying neonatal problems. Even neural networks aren't new to medicine. Study after study describes the success of these early AI diagnosticians. By the 1980s and 1990s, doctors were using CAD to give them a second opinion for diagnosing everything from lumbar hernias to gastric pain. Lodwick called his technique "computer-aided diagnosis," and CAD has been an invisible tool of medicine ever since. These were the logic-based days of early AI, so algorithms followed a sequence of rules to identify body parts: If there's an oval here attached to a thick line, we're looking at a hip bone connected to a thigh bone. Then, as he explained, these numbers could "be manipulated and evaluated by the digital computer."Īrmed with (rudimentary) image processing, in the 1970s radiologists began using machine vision to generate data directly from images. Lodwick published a paper in Radiology Society of America that described a technique he invented for predicting the survival span of lung cancer patients: Lodwick took X-rays and coded their features to represent tumor characteristics using numerical values. In 1963, a Midwestern radiologist named Gwilym S. In fact, AI has been quietly helping doctors treat diseases for almost its entire existence. AI's integration into our world will transform employment, economic activity, and possibly the character of our society.