In their study in this issue of BJUI, Hou et al. [1] use machine‐learning algorithms to evaluate several preoperative clinical variables (highlighting specific MRI findings of locally advanced prostate cancer) to determine whether lymph node involvement (LNI) could be present during radical prostatectomy, which would justify an extended pelvic lymph node dissection (PLND). This is a well‐designed study […]
Every month, the Editor-in-Chief selects an Article of the Month from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post. In addition to the […]
Current status of artificial intelligence applications in urology and their potential to influence clinical practice Abstract Objective To investigate the applications of artificial intelligence (AI) in diagnosis, treatment and outcome prediction in urologic diseases and evaluate its advantages over traditional models and methods. Materials and methods A literature search was performed after PROSPERO registration (CRD42018103701) […]
Wong et al. [1] evaluate 19 clinical variables (training data) and three supervised machine‐learning algorithms to predict early biochemical recurrence after robot‐assisted prostatectomy. They further compare the areas under the curve (AUCs) resulting from these algorithms with the AUC of a conventional Cox regression model and conclude that the machine‐learning algorithms can produce accurate disease prognosis, […]