Urology

Risk of major cardiovascular, renal, and thromboembolic events in patients with systemic sclerosis: A longitudinal cohort analysis.

An interpretable machine learning approach for detecting psoriatic arthritis in a UK primary care psoriasis cohort using electronic health records from the Clinical Practice Research Datalink.

OBJECTIVES: Develop an interpretable machine learning model to detect patients with newly diagnosed ...

AI-powered prostate cancer detection: a multi-centre, multi-scanner validation study.

OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect...

Generative artificial intelligence in oncology.

PURPOSE OF REVIEW: By leveraging models such as large language models (LLMs) and generative computer...

Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupu...

Air pollution and prostate cancer: Unraveling the connection through network toxicology and machine learning.

BACKGROUND: In recent years, air pollution has been demonstrated to be associated with the occurrenc...

Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department.

Radiocontrast media is a major cause of nephrotoxic acute kidney injury(AKI). Contrast-enhanced CT(C...

Development and evaluation of USCnet: an AI-based model for preoperative prediction of infectious and non-infectious urolithiasis.

BACKGROUND: Urolithiasis, a prevalent condition characterized by a high rate of incidence and recurr...

Accuracy of 7 artificial intelligence-based intraocular lens power calculation formulas in medium-long eyes: 2-center study.

OBJECTIVE: To compare accuracy of 7 artificial intelligence (AI)-based intraocular lens (IOL) power ...

Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.

INTRODUCTION: Hydrogel spacers (HS) are designed to minimise the radiation doses to the rectum in pr...

Using deep learning to differentiate among histology renal tumor types in computed tomography scans.

BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography ...

Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.

Feline chronic kidney disease (CKD) is one of the most frequently encountered diseases in veterinary...

Predicting the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis using a stacked ensemble machine learning model: a retrospective study based on the MIMIC database.

OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict t...

Comparison of the impact of rectal susceptibility artifacts in prostate magnetic resonance imaging on subjective evaluation and deep learning: a two-center retrospective study.

BACKGROUND: To compare the influence of rectal susceptibility artifacts on the subjective evaluation...

Predicting 90-day risk of urinary tract infections following urostomy in bladder cancer patients using machine learning and explainability.

This research aims to design and validate a machine learning model to predict the probability of uri...

Development and validation of a deep reinforcement learning algorithm for auto-delineation of organs at risk in cervical cancer radiotherapy.

This study was conducted to develop and validate a novel deep reinforcement learning (DRL) algorithm...

Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target.

BACKGROUND: The pathogenesis and progression of renal cell carcinoma (RCC) involve complex programme...

Machine learning selection of basement membrane-associated genes and development of a predictive model for kidney fibrosis.

This study investigates the role of basement membrane-related genes in kidney fibrosis, a significan...

Comparative analysis prediction of prostate and testicular cancer mortality using machine learning: accuracy study.

BACKGROUND: The mortality rates of prostate and testicular cancer are higher mortality in the northe...

Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.

Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been...

Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts.

BACKGROUND/OBJECTIVE: Longitudinal in vivo studies of murine xenograft models are widely utilized in...