Latest AI and machine learning research in urology for healthcare professionals.
Bacterial infections represent a critical threat to neonatal health, accounting for approximately 25% of neonatal mortality globally. Timely and precise diagnosis in infants aged 1 to 90Â days is essential to facilitate rapid intervention and prevent severe complications. This study aimed to develop and evaluate machine learning (ML) models for the early, non-invasive prediction of bacterial infect...
Urinary extracellular vesicles (uEVs) provide noninvasive biomarkers for liquid biopsy owing to their ability to reflect disease-associated molecular alterations. However, the accurate analysis of low-abundance uEV surface proteins in complex biological matrices remains a major analytical challenge. Here, we report a proximity-activated dual-cascade (PADC) biosensing platform that integrates a tar...
OBJECTIVES: The sensitivity of mammographic screening is lower for women with mammographically dense vs fatty breasts. We aimed to explore automated m...
To systematically characterize the global research trends, knowledge structure, thematic hotspots, and frontier evolution of artificial intelligence (...
BACKGROUND: Antibody-mediated rejection (AMR) is the main driver of late kidney allograft loss. Anti-HLA donor-specific antibodies (DSA) are strongly ...
Despite recent therapeutic advances, treatment options for advanced, therapy-resistant, and metastatic prostate cancer (PCa) remain limited. Here, we ...
OBJECTIVE: This study aimed to identify the factors contributing to Prolonged Length of Stay (PLOS) in intensive care units for sepsis patients combin...
Chronic Kidney Disease (CKD) is a global public health crisis, affecting over 800 million people worldwide. Driven primarily by diabetes and hypertens...
OBJECTIVES: To evaluate the feasibility and accuracy of an artificial intelligence (AI) model to assist surgeons through automated real-time detection...
OBJECTIVES: To predict spontaneous stone passage (SSP) in uncomplicated acute ureteric colic (AC) using non-contrast computed tomography (NCCT)-based ...
To map the development of robot-generated surgical data in urology and to assess how far the literature has progressed from engineering measurement to...
BACKGROUND: Liver enzyme biomarkers are known to contribute to the onset and progression of colorectal cancer. OBJECTIVE: To develop a novel oxidative...
Prostate cancer is a highly prevalent malignancy, and deep learning has significantly advanced di agnostic models based on multi-parametric MRI (mpMRI...
BACKGROUND: Overactive bladder (OAB) is a prevalent condition, particularly among women, characterized by urinary urgency, often accompanied by freque...
Chromosomal instability (CIN) drives clear cell renal cell carcinoma (ccRCC) progression, yet its upstream triggers remain elusive. To identify key dr...
OBJECTIVE: To predict self-care and mobility function at discharge from inpatient rehabilitation for adults with stroke using only variables from the ...
Standard slide-based two-dimensional (2D) histopathology severely undersamples spatially heterogeneous tissue, with each thin 2D section representing ...
To determine the optimal spatial-depth architecture for deep learning-radiomics (DLR) differentiation of fat-poor angiomyolipoma (fp-AML) from clear c...
Limited longitudinal field of view in cone-beam computed tomography (CBCT) remains a significant challenge for image-guided adaptive radiotherapy. We ...
BACKGROUND: Bladder cancer is the most common malignancy of the urinary tract and is often treated with radical cystectomy with lymph node dissection,...