Latest AI and machine learning research in urology for healthcare professionals.
Background The performance of a deep learning algorithm for lung cancer detection on chest radiographs in a health screening population is unknown. Purpose To validate a commercially available deep learning algorithm for lung cancer detection on chest radiographs in a health screening population. Materials and Methods Out-of-sample testing of a deep learning algorithm was retrospectively performed...
The objective of our study was to systematically review the literature about the application of artificial intelligence (AI) to renal mass characterization with a focus on the methodologic quality items. A systematic literature search was conducted using PubMed to identify original research studies about the application of AI to renal mass characterization. Besides baseline study characteristics...
OBJECTIVE: Bone scintigraphy has often been used to evaluate bone metastases. Its functionality is evident in detecting bone metastasis in patients wi...
BACKGROUND: Acute Kidney Injury (AKI) is a shared complication among Intensive Care Unit (ICU), marked by high cost, high morbidity and high mortality...
Prostate cancer is classified into different stages, each stage is related to a different Gleason score. The labeling of a diagnosed prostate cancer i...
Training of surgeons is essential for safe and effective use of robotic surgery, yet current assessment tools for learning progression are limited. Th...
BACKGROUND: A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (P...
BACKGROUND: This systematic review sought to compare the urogenital functions after laparoscopic (LAP) and robotic (ROB) surgery for rectal cancer.
The coronavirus disease 2019 (COVID-19) pandemic has generated large volumes of clinical data that can be an invaluable resource towards answering a n...
PURPOSE: Deep learning has shown great efficacy for semantic segmentation. However, there are difficulties in the collection, labeling and management ...
Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is pr...
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise...
BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective...
The prediction of post-prostatectomy incontinence (PPI) after robot-assisted radical prostatectomy (RARP) depends on multiple clinical, anatomical and...
BACKGROUND: The prevalence of acute kidney injury (AKI) in COVID-19 patients is high, with poor prognosis. Early identification of COVID-19 patients w...
BACKGROUND: The feasibility and efficacy of robot-assisted radical prostatectomy (RARP) in locally advanced prostate cancer (PCa) patients with iT3 le...
Proteases are often used as biomarkers of many pathologies as well as of microbial contamination and infection. Therefore, extensive efforts are devot...