Artificial intelligence and varicocelectomy: A new horizon for patient management? A narrative review

Abstract

Varicocele is a common entity found in 15% of men and is the most common reversible cause of male factor infertility. Guidelines have been developed to guide urologists in deciding which patients would benefit from varicocelectomy. Yet studies published over the last decade showed the emergence of predictors of success of varicocelectomy using nomograms and other predictive models with statistical analysis. The emergence of artificial intelligence (AI) and machine learning revolutionized the clinician's approach to medicine. The virtual branch of AI, represented by machine learning, has been a very exciting topic for clinicians and researchers over the last years, especially after the launching of ChatGPT-3.5. Urology has been at the forefront of integrating advances in AI into its everyday practice. We aim to shed light on the present literature describing the use of AI in predicting the outcomes of varicocelectomy. Machine learning is being used to predict the improvement in semen parameters after varicocelectomy. These algorithms are derived from studies and data present in the literature and predictive models developed throughout the last two decades and have a superior performance to that of traditional nomograms. However, these models require further research and validation but are anticipated to surpass the accuracy of all current resources, setting forward a new era of varicocele workup and management in the years to come. This paper offers a wide review on the current evidence behind varicocele surgery and the integration of AI in medicine, urology and its use in predicting improvement in sperm parameters post-varicocelectomy.

Keywords

artificial intelligence / artificial neural network / machine learning / varicocele / varicocelectomy

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The Author(s). UroPrecision published by John Wiley & Sons Australia, Ltd on behalf of Higher Education Press.