Urology

Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac Dysfunction.

BACKGROUND: Predicting risk of cancer therapy-related cardiac dysfunction (CTRCD) remains challenging. OBJECTIVES: The purpose of this study was to assess if deep learning (DL) approaches using cardiac magnetic resonance (CMR) images before cancer therapy can predict subsequent CTRCD and compare them with clinical and conventional imaging models. METHODS: Women with HER2+ breast cancer receiving a...

Displaced minds: ecologies of depression.

This issue of the Biomedical Journal explores emerging perspectives across neuropsychiatry, metabolism, aging, regenerative medicine, artificial intelligence, and chronic inflammatory disease. Featured contributions examine epigenetic and neuroendocrine mechanisms in depression, including the antidepressant-like effects of magnolol in chronic stress-induced models and the potential relevance of sh...

Artificial Intelligence-Powered Cystoscopy Diagnostic Support System: Clinical Application of Multiarchitecture Deep Learning Models.

PURPOSE: Cystoscopy is a crucial diagnostic tool in urology for the detection and evaluation of bladder lesions. However, its diagnostic accuracy (ACC...

Age-Dependent z Scores and eGFR-Adjusted Reference Ranges for Neurofilament Light: A Practical Approach for Clinical Laboratories.

BACKGROUND: Neurofilament light (NfL) has emerged as a sensitive biomarker of neuroaxonal damage across a wide spectrum of neurological conditions, in...

Automated recognition of surgical phases in robot-assisted radical prostatectomy using a Hiera-based vision transformer.

OBJECTIVES: To construct a reliable robot-assisted radical prostatectomy (RARP) surgical phase-recognition model and sought to deploy the model within...

Interpretable machine learning model for predicting hemorrhage following ultrasound-guided percutaneous renal biopsy: a multicenter study.

OBJECTIVE: This study aims to develop and validate an interpretable machine learning (ML) model for predicting post-procedural hemorrhage (PH) after u...

Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer.

OBJECTIVE: Postoperative biochemical recurrence (BCR) of prostate cancer (PCa) remains a major clinical challenge, and traditional risk assessment sys...

Machine-learning algorithms identifies sTREM1 has a key biomarker for outcome prediction in critically ill.

INTRODUCTION: Prognostic assessment in critically ill patients traditionally relies on severity scores or single biomarkers, each with limited ability...

Assessing multiple chatGPT versions on novel content in the Taiwan urology board examination: accuracy, speed, and domain-specific performance.

PURPOSE: Large language models demonstrate increasing utility in healthcare; however, their capacity to handle newly developed medical content beyond ...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...

Usability and Usefulness of Machine Learning-Based Clinical Decision Support Software in Primary Care: Survey of Users in a Prospective Observational Study.

BACKGROUND: The successful implementation of decision support systems promises to enhance high-quality care. However, the successful implementation of...

Machine learning-based prediction of a high-risk kidney function trajectory class after acute kidney injury.

OBJECTIVES: Monitoring kidney function after acute kidney injury (AKI) hospitalisation is essential for identifying patients at risk of rapid progress...

Re: Navid Roessler, Marcin Miszczyk, Keiichiro Miyajima, et al. Harnessing Artificial Intelligence for Risk Stratification and Outcome Prediction in Urologic Cancers: A Systematic Review. Eur Urol Focus 2025; S2405-4569(25)00362-1. In press. http://dx.doi.org/10.1016/j.euf.2025.12.007.

[MRI-based deep learning model for preoperative prediction of urothelial carcinoma with variant histology of bladder: a retrospective, multicenter study].

Objectives: To develop a deep learning model based on magnetic resonance imaging (MRI) for the preoperative prediction of urothelial carcinoma with va...

Evaluating Iterative Deep Learning as a Labeling-Efficient Strategy for Tubular Segmentation in Digital Nephropathology.

Chronic kidney disease (CKD) is a prevalent condition worldwide and a significant global health burden that is expected to increase in the coming deca...

Artificial Intelligence in Kidney Transplant Pathology: Current Evidence, Limitations, and Relevance to the Banff Framework.

The Banff Classification, established in 1991, provides a global standard for diagnosing and grading kidney transplant pathology, evolving through reg...

Diagnostic value of integrated albumin-to-leukocyte ratio risk modeling stratification and machine learning approaches for prediction of spontaneous bacterial peritonitis in cirrhotic patients.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) remains a life-threatening complication of liver cirrhosis, requiring accurate and rapid predictio...

Epigenetic-Metabolic interplay in chronic kidney disease mortality: insights from grimage acceleration and transcriptomic profiling.

BACKGROUND: Chronic kidney disease (CKD) is associated with a substantially elevated risk of mortality. Although GrimAge acceleration (GAA) and metabo...

Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.

Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagn...

Elucidating the pathogenic mechanism underlying plasticizer-induced chronic kidney disease via integrated network toxicology and machine learning.

Plasticizers are ubiquitous plastic additives that have been linked to multiple adverse health outcomes and elevated risks of chronic kidney disease (...