Urology

Letter to the editor for the article "Combination of urinary biomarkers and machine-learning models provided a higher predictive accuracy to predict long-term treatment outcomes of patients with interstitial cystitis/bladder pain syndrome".

Effectiveness and Cost-effectiveness of Artificial Intelligence-assisted Pathology for Prostate Cancer Diagnosis in Sweden: A Microsimulation Study.

BACKGROUND AND OBJECTIVE: Image-based artificial intelligence (AI) methods have shown high accuracy in prostate cancer (PCa) detection. Their impact on patient outcomes and cost effectiveness in comparison to human pathologists remains unknown. Our aim was to evaluate the effectiveness and cost-effectiveness of AI-assisted pathology for PCa diagnosis in Sweden.

Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol.

OBJECTIVES: To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa) in comparison to the standard multiparametric (mp...

Deep-learning-based sampling position selection on color Doppler sonography images during renal artery ultrasound scanning.

Accurate selection of sampling positions is critical in renal artery ultrasound examinations, and the potential of utilizing deep learning (DL) for as...

A machine learning approach using stone volume to predict stone-free status at ureteroscopy.

INTRODUCTION: To develop a predictive model incorporating stone volume along with other clinical and radiological factors to predict stone-free (SF) s...

Cherry on Top or Real Need? A Review of Explainable Machine Learning in Kidney Transplantation.

Research on solid organ transplantation has taken advantage of the substantial acquisition of medical data and the use of artificial intelligence (AI)...

Stacked neural network for predicting polygenic risk score.

In recent years, the utility of polygenic risk scores (PRS) in forecasting disease susceptibility from genome-wide association studies (GWAS) results ...

Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar.

The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of s...

Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer.

BACKGROUND: Bladder cancer (BCa) is among the most prevalent malignant tumors affecting the urinary system. Due to its highly recurrent nature, standa...

Machine Learning-Based Mortality Prediction in Chronic Kidney Disease among Heart Failure Patients: Insights and Outcomes from the Jordanian Heart Failure Registry.

Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the qualit...

Evaluation of the Current Status of Artificial Intelligence for Endourology Patient Education: A Blind Comparison of ChatGPT and Google Bard Against Traditional Information Resources.

Artificial intelligence (AI) platforms such as ChatGPT and Bard are increasingly utilized to answer patient health care questions. We present the fir...

Automated Analysis of Split Kidney Function from CT Scans Using Deep Learning and Delta Radiomics.

Differential kidney function assessment is an important part of preoperative evaluation of various urological interventions. It is obtained through d...

Evaluating the predictive value of angiogenesis-related genes for prognosis and immunotherapy response in prostate adenocarcinoma using machine learning and experimental approaches.

BACKGROUND: Angiogenesis, the process of forming new blood vessels from pre-existing ones, plays a crucial role in the development and advancement of ...

Artificial Intelligence for Urology Research: The Holy Grail of Data Science or Pandora's Box of Misinformation?

Artificial intelligence tools such as the large language models (LLMs) Bard and ChatGPT have generated significant research interest. Utilization of ...

Machine learning algorithm predicts urethral stricture following transurethral prostate resection.

PURPOSE: To predict the post transurethral prostate resection(TURP) urethral stricture probability by applying different machine learning algorithms u...

Perception of cure in prostate cancer: human-led and artificial intelligence-assisted landscape review and linguistic analysis of literature, social media and policy documents.

BACKGROUND: Understanding stakeholders' perception of cure in prostate cancer (PC) is essential to preparing for effective communication about emergin...

Robust prostate disease classification using transformers with discrete representations.

PURPOSE: Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural n...

Application of Natural Language Processing in Electronic Health Record Data Extraction for Navigating Prostate Cancer Care: A Narrative Review.

Natural language processing (NLP)-based data extraction from electronic health records (EHRs) holds significant potential to simplify clinical manage...

The influence of manual segmentation strategies and different phases selection on machine learning-based computed tomography in renal tumors: a systematic review and meta-analysis.

BACKGROUND: Delineating the region/volume of interest (ROI/VOI) and selecting the phases are of importance in developing machine learning (ML). The re...

Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.

Radiation treatment of cancers like prostate or cervix cancer requires considering nearby bone structures like vertebrae. In this work, we present and...