Artificial intelligence in functional urology: how it may shape the future

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Bentellis, Imad | Guerin, Sonia | Khene, Zine-Eddine | Khavari, Rose | Peyronnet, Benoit

Edité par CCSD ; Lippincott, Williams & Wilkins -

International audience. Purpose of review The aim of the present manuscript is to provide an overview on the current state of artificial intelligence (AI) tools in either decision making, diagnosis, treatment options, or outcome prediction in functional urology. Recent findings Several recent studies have shed light on the promising potential of AI in functional urology to investigate lower urinary tract dysfunction pathophysiology but also as a diagnostic tool by enhancing the existing evaluations such as dynamic magnetic resonance imaging or urodynamics. AI may also improve surgical education and training because of its automated performance metrics recording. By bringing prediction models, AI may also have strong therapeutic implications in the field of functional urology in the near future. AI may also be implemented in innovative devices such as e-bladder diary and electromechanical artificial urinary sphincter and could facilitate the development of remote medicine. Over the past decade, the enthusiasm for AI has been rising exponentially. Machine learning was well known, but the increasing power of processors and the amount of data available has provided the platform for deep learning tools to expand. Although the literature on the applications of AI technology in the field of functional urology is relatively sparse, its possible uses are countless especially in surgical training, imaging, urodynamics, and innovative devices.

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