The concept of artificial intelligence (AI) elicits futuristic images in the minds of many, perhaps reminding them of films about dystopian worlds. References to AI go back to the 1950s when British computer scientist Alan Turing developed the Church-Turing thesis, which states that natural numbers cannot be computed by a human being unless they are computable by a Turing machine (computer). Due to the fact that computers were not powerful at the time, applications were limited.[1]

John McCarthy, esteemed mathematician and computer scientist, coined the term “artificial intelligence” in 1956 during a highly attended summer workshop in Dartmouth. He complained that, “as soon as it works, no one calls it AI anymore.”[2] By 1959, machines began playing checkers better than humans. In 1965, McCarthy founded the Stanford Artificial Intelligence Laboratory, where groundbreaking research was conducted in computing and automation.[3]

AI took a back seat during the 1970s and 1980s (the so-called AI winters), but major breakthroughs occurred soon afterward. The 1990s were the dawn of faster computers and big data. In 1997, Deep Blue—a chess-playing supercomputer developed by International Business Machines (IBM) Corporation—defeated reigning world champion Gary Kasparov in a pair of six-game chess matches.[1] IBM later developed Watson in 2011, the supercomputer that defeated two reigning champions at Jeopardy! This was also the year that McCarthy passed away.

AI in radiology, though still in its infancy, has made tremendous strides. AI has been investigated in interventional radiology (IR) as well, though to a lesser extent. This article will summarize the role of AI in radiology and IR thus far and delve into its future applications.

Article published online:
31 August 2022

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