Urology

New Targets for Imaging in Nuclear Medicine.

Nuclear medicine is rapidly evolving with new molecular imaging targets and advanced computational tools that promise to enhance diagnostic precision and personalized therapy. Recent years have seen a surge in novel PET and SPECT tracers, such as those targeting prostate-specific membrane antigen (PSMA) in prostate cancer, fibroblast activation protein (FAP) in tumor stroma, and tau protein in neu...

Pix2Pix generative-adversarial network in improving the quality of T2-weighted prostate magnetic resonance imaging: a multi-reader study.

PURPOSE: To assess the performance and feasibility of generative deep learning in enhancing the image quality of T2-weighted (T2W) prostate magnetic resonance imaging (MRI).

Machine learning models for acute kidney injury prediction and management: a scoping review of externally validated studies.

Despite advancements in medical care, acute kidney injury (AKI) remains a major contributor to adverse patient outcomes and presents a significant cha...

Innovative, Technology-Driven, Digital Tools for Managing Pediatric Urinary Incontinence: Scoping Review.

BACKGROUND: Urinary incontinence affects approximately 7% to 10% of children during the day and 9% to 12% of children during the night. Treatment main...

Associations between urinary and blood heavy metal exposure and heart failure in elderly adults: Insights from an interpretable machine learning model based on NHANES (2003-2020).

BACKGROUND: The relationship between heavy metal exposure and heart failure is complex and poorly understood. This study employs machine learning tech...

PSMA PET/CT for prostate cancer diagnosis: current applications and future directions.

Prostate cancer (PCa) requires improved diagnostic strategies beyond conventional imaging. This review aimed to evaluate the role of prostate-specific...

Multi-objective optimization framework to plan laser ablation procedure for prostate tumors through a genetic algorithm.

BACKGROUND AND OBJECTIVES: Prostate cancer is the most common form of cancer in the male population. While the survival rate is high, many patients un...

Development and external validation of a model for post-endoscopic retrograde cholangiopancreatography pancreatitis.

Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a common complication in patients undergoing ERCP for choledocholithi...

GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma.

Glioblastoma (GBM) is a fatal brain cancer known for its rapid and aggressive growth, with some studies indicating that females may have better surviv...

Development and validation of a machine learning-based risk model for metastatic disease in nmCRPC patients: a tumor marker prognostic study.

BACKGROUND: Nonmetastatic castration-resistant prostate cancer (nmCRPC) is a clinical challenge due to the high progression rate to metastasis and mor...

Identification of Factors Affecting Prostate Cancer Using Machine Learning Methods: A Systematic Review.

BACKGROUND: Prostate cancer is identified as the second cause of malignancy worldwide and the fifth cause of death among men. Considering the upward t...

The Use of Maximum-Intensity Projections and Deep Learning Adds Value to the Fully Automatic Segmentation of Lesions Avid for [F]FDG and [Ga]Ga-PSMA in PET/CT.

This study investigated the added value of using maximum-intensity projection (MIP) images for fully automatic segmentation of lesions using deep lear...

Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning.

Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared wi...

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.

Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive underst...

Artificial Intelligence in Prostate Cancer Diagnosis on Magnetic Resonance Imaging: Time for a New PARADIGM.

Artificial intelligence (AI) may provide a solution for improving access to expert, timely, and accurate magnetic resonance imaging (MRI) interpretati...

Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis.

We aim to characterize gender authorship in urology-related artificial intelligence (AI) research. A retrospective review was performed using MEDLINE,...

Feature selection for classification based on machine learning algorithms for prostate cancer.

Microarray technology has transformed the biotechnological research to next level in the recent years. It provides the expression levels of various ge...

Pioneering AI-guided fluorescence-like navigation in urological surgery: real-time ureter segmentation during robot-assisted radical cystectomy using convolutional neural network.

Artificial intelligence (AI)-driven intraoperative navigation in urological surgery can enhance surgical precision through real-time structure identif...

Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector.

Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection an...

Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic ...