Soon, AI simulations of the circuit of monomorphic ventricular tachycardia may be used to guide catheter ablation, or even stereotactic radioablation for a vast number of patients. There is now emerging evidence that AI may support diagnostics in electrophysiology by automating common clinical tasks or aiding complex tasks using deep neural networks that are superior to currently implemented computerised algorithms.
After all, Gary Kasparov did lose at chess to IBM’s Deep Blue.įor clinicians – in particular electrophysiologists and arrhythmia experts – the power of AI has become equally apparent.
Today, philosophers and futurists such as Nick Bostrom and Ray Kurzweil speak not of AI, but of superintelligence, far exceeding the capacity and might of the human brain. The first published algorithm ever specifically tailored for implementation on a computer was published by Ada Lovelace – the disciple of Charles Babbage and daughter of the great philhellene Lord Byron – in 1843. The potential impact of artificial intelligence (AI) has been realised by even its staunchest critics, and the possibility of a wonder thinking machine, ‘the Master Algorithm’ as computer scientist Pedro Domingo called it, is no longer just science fiction.ĭespite the recent explosion of interest in AI, the reality is that progress has been moving along for at least 180 years. It is remarkable that performing that same search only a year later yields almost 28,500 further citations, with the total now – as of 2 October 2021 – being 139,304 publications. At that time, the search yielded 110,855 publications. In October 2020, for a previous editorial in this journal, the term ‘artificial intelligence’ was searched in the National Library of Medicine via PubMed.
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