Latest AI and machine learning research in urology for healthcare professionals.
In this paper, we explore the application of ensemble optimal control to derive enhanced strategies for pharmacological cancer treatment. In particular, we focus on moving beyond the classical clinical approach of giving the patient the maximal tolerated drug dose (MTD), which does not properly exploit the fight among sensitive and resistant cells for the available resources. Here, we employ a L...
Identifying \textit{Anastrepha} species from the \textit{pseudoparallela} group is problematic due to morphological similarities among species and a broad geographic variation. This group comprises $31$ species of fruit flies and pests affecting passion fruit crops. Identifying these species utilises the morphological characteristics of the specimens' wings and aculeus tips. Considering the impo...
Lymph node (LN) assessment is an essential task in the routine radiology workflow, providing valuable insights for cancer staging, treatment plannin...
Medical image segmentation is essential for clinical diagnosis, surgical planning, and treatment monitoring. Traditional approaches typically strive...
Access to real-world healthcare data is limited by stringent privacy regulations and data imbalances, hindering advancements in research and clinica...
This study presents a 3D flow-matching model designed to predict the progression of the frozen region (iceball) during kidney cryoablation. Precise ...
Privacy-preserving medical decision support for kidney disease requires localized deployment of large language models (LLMs) while maintaining clini...
Objective:This study introduces a residual error-shifting mechanism that drastically reduces sampling steps while preserving critical anatomical det...
BACKGROUND: We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented ki...
Purpose To evaluate the performance of Physics-Informed Autoencoder (PIA), a self-supervised deep learning model, in measuring tissue-based biomarkers...
BACKGROUND: Chronic rejection forms the leading cause of late graft loss in pediatric kidney transplant recipients. Despite improvement in short-term ...
BACKGROUND: In recent years, artificial intelligence (AI) applications have been increasingly used as sources of medical information, alongside their ...
In small animal practice, patients often present with urinary lithiasis, and prediction of urolith composition is essential to determine the appropria...
Background Although artificial intelligence is actively being developed for prostate MRI, few studies have prospectively validated these tools. Purpos...
This work aimed to evaluate both the usefulness and user acceptance of five gradient-based explainable artificial intelligence (XAI) methods in the us...
Background The ScreenTrustCAD trial was a prospective study that evaluated the cancer detection rates for combinations of artificial intelligence (AI)...
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution...
The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole s...
In the current paper, we will focus on requirements to ensure big data can advance the outcomes of our patients suffering from kidney disease. The ass...
Existing point cloud completion methods, which typically depend on predefined synthetic training datasets, encounter significant challenges when app...