Machine learning in renal cell carcinoma research: the promise and pitfalls of 'renal‐izing' the potential of artificial intelligence.

While ML techniques provide new opportunities in the field of RCC prognostication, it is imperative to standardize and improve the quality of reporting of these novel artificial intelligence algorithms, as well as to thoroughly validate them before integration into shared decision making in daily clinical practice. Abbreviations AUC area under the curve ML machine learning SHAP Shapley additive explanations STREAM-URO Standardized Reporting of Machine Learning Applications in Urology Artificial intelligence and machine learning (ML) are increasingly applied to the study of patients with RCC [[1]]. The Standardized Reporting of Machine Learning Applications in Urology (STREAM-URO) framework was developed to provide a set of recommendations to standardize the way in which ML studies are reported [[8]]. [Extracted from the article]