Abstract
ABSTRACTArtificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as good as, or even better than, those drawn by humans. AI is already part of our daily life; it is behind face recognition technology, speech recognition in virtual assistants (such as Amazon Alexa, Apple's Siri, Google Assistant and Microsoft Cortana) and self‐driving cars. AI software has been able to beat world champions in chess, Go and recently even Poker. Relevant to our community, it is a prominent source of innovation in healthcare, already helping to develop new drugs, support clinical decisions and provide quality assurance in radiology. The list of medical image‐analysis AI applications with USA Food and Drug Administration or European Union (soon to fall under European Union Medical Device Regulation) approval is growing rapidly and covers diverse clinical needs, such as detection of arrhythmia using a smartwatch or automatic triage of critical imaging studies to the top of the radiologist's worklist. Deep learning, a leading tool of AI, performs particularly well in image pattern recognition and, therefore, can be of great benefit to doctors who rely heavily on images, such as sonologists, radiographers and pathologists. Although obstetric and gynecological ultrasound are two of the most commonly performed imaging studies, AI has had little impact on this field so far. Nevertheless, there is huge potential for AI to assist in repetitive ultrasound tasks, such as automatically identifying good‐quality acquisitions and providing instant quality assurance. For this potential to thrive, interdisciplinary communication between AI developers and ultrasound professionals is necessary. In this article, we explore the fundamentals of medical imaging AI, from theory to applicability, and introduce some key terms to medical professionals in the field of ultrasound. We believe that wider knowledge of AI will help accelerate its integration into healthcare. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
Highlights
Artificial intelligence (AI) is described as the ability of a computer program to perform processes associated with human intelligence, such as reasoning, learning, adaptation, sensory understanding and interaction[1]
Deep learning performs well in image pattern recognition and solutions based on this approach can benefit healthcare professionals who depend heavily on information obtained from images, such as radiographers, pathologists and sonologists
We have presented an overview of AI technology and some of the issues related to the introduction of this emerging technology into clinical practice, in the context of ultrasound in obstetrics and gynecology
Summary
Artificial intelligence (AI) is described as the ability of a computer program to perform processes associated with human intelligence, such as reasoning, learning, adaptation, sensory understanding and interaction[1]. In his seminal paper published in 19502, Alan Turing introduced a test ( called ‘the Turing test’) in which, if an evaluator cannot distinguish whether intelligent behavior is exhibited by a machine or a human, the machine is said to have passed the test[2]. Traditional computational algorithms are software programs that follow a sequence of rules and perform an identical function every time, such as an electronic calculator: ‘if this is the input, that is the output’. Major milestones in the history of AI include the Deep Blue computer outmatching the world chess champion, Gary Kasparov, in 1997 and AlphaGo defeating one of the best players (ranked 9-dan) of the ancient Chinese game of Go, Lee Sedol, in 20164
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