Latest AI and machine learning research in urology for healthcare professionals.
In this paper, we trained a set of Portuguese clinical word embedding models of different granularities from multi-specialty and multi-institutional clinical narrative datasets. Then, we assessed their impact on a downstream biomedical NLP task of Urinary Tract Infection disease identification. Additionally, we intrinsically evaluated our main model using an adapted version of Bio-SimLex for the P...
Due to various etiologies and pathogenesis of kidney diseases, an invasive procedure called renal biopsy may be needed to determine the specific type of kidney disease, its severity, and the best treatment for it. This study aims to detmine if a text understanding technology based on admission records can recommend such an invasive procedure objectively. To understand clinical documents from nephr...
Clinical and pathological stage are defining parameters in oncology, which direct a patient's treatment options and prognosis. Pathology reports conta...
Advanced chronic kidney disease (CKD) requires routine renal replacement therapy (RRT) that involves hemodialysis (HD) which may cause increased risk ...
In this research, we exploit an image-based deep learning framework to distinguish three major subtypes of renal cell carcinoma (clear cell, papillary...
Cardiovascular imaging is going to change substantially in the next decade, fueled by the deep learning revolution. For medical professionals, it is i...
Artificial intelligence (AI) - the ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data - is revolution...
PURPOSE: Cancer pathology findings are critical for many aspects of care but are often locked away as unstructured free text. Our objective was to dev...
Prior studies have used vital signs and laboratory measurements with conventional modeling techniques to predict acute kidney injury (AKI). The purpos...
Prostate cancer is one of the leading causes of death around the world. The manual Gleason grading of prostate cancer after histological analysis of s...
In urology endoscopic procedures, the Ureteral Orifice (UO) finding is crucial but may be challenging for inexperienced doctors. Generally, it is diff...
The ability to accurately recognize elementary surgical gestures is a stepping stone to automated surgical assessment and surgical training. In this p...
PURPOSE: The purpose of the study was to propose a deep transfer learning (DTL)-based model to distinguish indolent from clinically significant prosta...
PURPOSE: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial ...
The failure to predict kidney toxicity of new chemical entities early in the development process before they reach humans remains a critical issue. He...
Pathologic grading plays a key role in prostate cancer risk stratification and treatment selection, traditionally assessed from systemic core needle b...
PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize mammographic reporting to assess cancer risk and ...
OBJECTIVE: Robot-assisted laparoscopic radical prostatectomy (RARP) is nowadays considered the main surgical option for localized prostate cancer (P...
OBJECTIVE: To review the literature evaluating the role of the extended pelvic lymph node dissectione PLND during robot assisted radical prostatectomy...
The urology community has adopted robot-assisted radical prostatectomy (RARP) as the most preferred surgical therapeutic approach in the management of...