Technology is continually opening new doors within healthcare, from simple things such as faster ways of booking a doctor’s appointment to such large-scale projects like developing preventative treatments for cancer, dementia and other illnesses. The latter is where artificial intelligence, or, AI, really comes into play.
THE TERM “AI” refers to advanced technologies that enable a computer to complete tasks that normally require human intelligence. These machines mimic “cognitive” functions that we typically associate with the human mind, such as “learning”, “sensing” and “problem solving,” through recognising intricate patterns within data.
Diagnosis, an understanding of the probability for presence of illness, depends on data, as medical journal, The Lancet explains. “Its collection, integration, and interpretation enables accurate classification of clinical presentations into an accepted disease category. Human diagnosticians achieve acceptable accuracy in such classification tasks through the learning of diagnostic rules, followed by training on real cases.”
In AI, on the other hand, artificial neural networks (so called because of their resemblance to human ones) detect the intricate structures and patterns within large and complex sets of data, such as medical images, for example. Yet arguably the most fascinating feature of these “neural networks” is their ability to evolve on the basis of experience, ie, as they receive and process more and more data, their ability to recognise, classify and—most crucially—predict future patterns becomes more fine-tuned.
この記事は Reader's Digest UK の May 2020 版に掲載されています。
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