Do you think we're gonna be replaced?

It is almost 40 years since a full-body magnetic resonance imaging (MRI) machine was used for the first time to scan a patient and generate diagnostic-quality images. The scanner and signal processing methods needed to produce an image were devised by a team of medical physicists including John Mallard, Jim Hutchinson, Bill Edelstein and Tom Redpath at the University of Aberdeen, leading to the widespread use of the MRI scanner, now a ubiquitous tool in radiology departments across the world. MRI was a game-changer in medical diagnostics because it didn't require exposure to ionising radiation (such as X-rays), and could generate images on multiple cross-sections of the body with superb definition of soft tissues. This allowed, for example, the direct visualisation of the spinal cord for the first time. Most people today will have undergone an MRI or know somebody who has.

Many of us come across the term AI almost on a daily basis. It is a term that we associate with self-driving cars, talking robots and with future in general. Many of us in the medical fraternity are already looking at this as a potential threat. But, what exactly does this mean to medical practice? Extreme scenarios like robots taking over surgery without human interaction is unlikely. But there are certain aspects of medicine that computers are quite good at.

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Radiologists bring home $395,000 each year, on average. In the near future, however, those numbers promise to drop to $0. Don't blame Obamacare, however, or even Trumpcare (whatever that turns out to be), but rather blame the rise of machine learning and its applicability to these two areas of medicine that are heavily focused on pattern matching, a job better done by a machine than a human. This is the argument put forward by Dr. Ziad Obermeyer of Harvard Medical School and Brigham and Women's Hospital and Ezekiel Emanuel, PhD, of the University of Pennsylvania, in an article for the New England Journal of Medicine, one of the medical profession's most prestigious journals. Machine learning will produce big winners and losers in healthcare, according to the authors, with radiologists and pathologists among the biggest losers.

Artificial intelligence--the mimicking of human cognition by computers--was once a fable in science fiction but is becoming reality in medicine. The combination of big data and artificial intelligence, referred to by some as the fourth industrial revolution,1 will change radiology and pathology along with other medical specialties. Although reports of radiologists and pathologists being replaced by computers seem exaggerated,2 these specialties must plan strategically for a future in which artificial intelligence is part of the health care workforce. Radiologists have always revered machines and technology. In 1960, Lusted predicted "an electronic scanner-computer to examine chest photofluorograms, to separate the clearly normal chest films from the abnormal chest films."3