Evolution Although AI has only become mainstream in the public consciousness in recent years, as an area of computer science, it’s far from new. The term artificial intelligence was coined in 1956 and the Department of Defense began exploring possible uses in the 1960s. The Defense Advanced Research Project Agency took advantage of AI to do street-mapping projects in the 1970s, and the first application in health care came in the same decade with the development of an AI program that identified blood infections. In 1979, the American Association for the Advancement of Artificial Intelligence ( aaai.org ) came into being, and AI continued to advance in the 1980s and ‘90s with research on methods to collect and process data faster and assist in making some medical procedures more precise. For instance, robotic surgery such as the DaVinci system, which augments a
AI is specialized software that allows computers to replicate human intelligence by using algorithms—the commands a computer follows—to complete tasks. It has access to large volumes of data sets and, when programmed with the correct questions, it can use the data to focus on solving a specific problem. As it processes masses of information, it also learns from it to do its assigned tasks better, so its ability improves over time. It’s able to analyze large quantities of data much faster than people and is typically more accurate, partly because machines don’t get tired or have interruptions to the workflow the way multi-tasking humans do. The goal, though, isn’t to replace people. Rather, in health care, AI is a tool that assists medical professionals by providing valuable information quickly so they can use it to enhance their decision-making—resulting in better outcomes and benefiting patients.
surgical team’s capabilities, was in use in operating rooms in Europe in 1999 and received approval from the U.S. Food and Drug Administration in 2000. Progress was slow but steady until 2011, and then AI began to get the public’s attention when breakthroughs in deep learning— also known as strong AI—modeled on the human brain made it possible for computers to perform tasks using images, text and sound. Its use accelerated, and several areas of health care, including primary care, radiology, screening, the diagnosis of disease and telemedicine, now use it as an integral part of their practices. When time counts Patients having strokes lose more than a million brain cells a minute, so the faster they get treatment the better. AI is a gamechanger in such cases, because in providing images quickly, it allows a physician to put a treatment plan into action sooner than is possible with traditional methods. Stroke specialists in Sutter Health’s network are using an AI-based platform that automatically processes CT scans to identify large blood-vessel clots and deliver clear images that are easy to interpret. “Hospital stroke teams and emergency department personnel receive these results in three minutes or less,” says Laura Wilt, a senior vice president and Sutter’s chief digital officer. “This rapid response enables doctors to diagnose the stroke type and plan treatment faster and more accurately,” she explains, giving victims a better chance of recovery. In imaging, AI can find subtle abnormalities that are difficult for the human eye to see. The National Institutes of Health, a federal agency noted for its medical research, reports that physicians are using retinal scans to identify diabetic retinopathy, a complication of a type
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20 NorthBaybiz
February 2024
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