STRUČNI članak / expert article*
Importance of radiology as a profession is massive. Rarely will any hospitalised patient finish his journey without visiting the radiology department. So, if we develop a system that will help radiology to increase productivity and accuracy while keeping the patient safe, the effects of this technology will also be massive. Artificial Intelligence (AI) has shown a potential to be one possible technology to revolutionise the radiology service.
Over the last ten years, publications on AI in radiology have increased from 100–150 per year to 700–800 per year (Pesapane et al., 2018) highlighting the importance of the topic. In 2016 was predicted that „machine learning will displace much of the work of radiologists and anatomical pathologists“ (Obermeyer and Emanuel, 2016), and that machines will replace doctors because „when professional work is broken down into component parts, many of the tasks involved turn out to be routine and process-based. They do not, in fact, call for judgment, creativity, or empathy“ (Susskind and Susskind, 2016). There is more evidence of scientists overestimated the potential of AI, and probably the most famous one was from one of the AI pioneers, winner of the Association for Computing Machinery Turing Award, who stated in 2016: „People should stop training radiologists now“ (Geoff Hinton: On Radiology – YouTube, 2016).
Today, the predictions are alleviated, and some of the scientists mentioned already revised their forecasts (Hinton, 2018). Nevertheless, it has been shown that radiology professionals still lack exposure to current scientific medical articles on artificial intelligence.