Urology

A multicentre implementation trial of an Artificial Intelligence-driven biomarker to inform Shared decisions for androgen deprivation therapy in men undergoing prostate radiotherapy: the ASTuTE protocol.

BACKGROUND: Androgen deprivation therapy (ADT) improves outcomes in men undergoing definitive radiotherapy for prostate cancer but carries significant toxicities. Clinical parameters alone are insufficient to accurately identify patients who will derive the most benefit, highlighting the need for improved patient selection tools to minimize unnecessary exposure to ADT's side effects while ensuring...

Assessing ChatGPT Responses to Frequently Asked Patient Questions in Reconstructive Urology.

INTRODUCTION: Artificial intelligence (such as Chat Generative Pretrained Transformer [ChatGPT]) augments patient education on medical topics, including reconstructive surgery. In this study, we assess the information, misinformation, and readability of ChatGPT responses to reconstructive urology questions. We also evaluate prompt engineering to optimize responses.

Artificial intelligence and patient education.

PURPOSE OF REVIEW: Artificial intelligence (AI) chatbots are increasingly used as a source of information. Our objective was to review the literature ...

Liver fibrosis progression analyzed with AI predicts renal decline.

BACKGROUND & AIMS: The relationship between biopsy-proven liver fibrosis progression and renal function decline in patients with metabolic dysfunction...

Does Deep Learning Reconstruction Improve Ureteral Stone Detection and Subjective Image Quality in the CT Images of Patients with Metal Hardware?

Diagnosing ureteral stones with low-dose CT in patients with metal hardware can be challenging because of image noise. The purpose of this study was ...

Which current chatbot is more competent in urological theoretical knowledge? A comparative analysis by the European board of urology in-service assessment.

INTRODUCTION: The European Board of Urology (EBU) In-Service Assessment (ISA) test evaluates urologists' knowledge and interpretation. Artificial Inte...

Use of deep learning-accelerated T2 TSE for prostate MRI: Comparison with and without hyoscine butylbromide admission.

OBJECTIVE: To investigate the use of deep learning (DL) T2-weighted turbo spin echo (TSE) imaging sequence with deep learning acceleration (T2DL) in p...

An accurate and trustworthy deep learning approach for bladder tumor segmentation with uncertainty estimation.

BACKGROUND AND OBJECTIVE: Although deep learning-based intelligent diagnosis of bladder cancer has achieved excellent performance, the reliability of ...

Machine learning prediction of glaucoma by heavy metal exposure: results from the National Health and Nutrition Examination Survey 2005 to 2008.

Using follow-up data from the National Health and Nutrition Examination Survey (NHANES) database, we have collected information on 2572 subjects and u...

Development of a deep learning system for predicting biochemical recurrence in prostate cancer.

BACKGROUND: Biochemical recurrence (BCR) occurs in 20%-40% of men with prostate cancer (PCa) who undergo radical prostatectomy. Predicting which patie...

M-NET: Transforming Single Nucleotide Variations Into Patient Feature Images for the Prediction of Prostate Cancer Metastasis and Identification of Significant Pathways.

High-performance prediction of prostate cancer metastasis based on single nucleotide variations remains a challenge. Therefore, we developed a novel b...

An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen ...

Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images.

Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classifica...

Discovering Vitamin-D-Deficiency-Associated Factors in Korean Adults Using KNHANES Data Based on an Integrated Analysis of Machine Learning and Statistical Techniques.

: Vitamin D deficiency (VDD) is a global health concern associated with metabolic disease and immune dysfunction. Despite known risk factors like limi...

The implementation of knowledge-based planning with partial OAR contours for prostate radiotherapy.

PURPOSE: Intra- and inter-observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to addr...

Revolutionizing prostate cancer therapy: Artificial intelligence - Based nanocarriers for precision diagnosis and treatment.

Prostate cancer is one of the major health challenges in the world and needs novel therapeutic approaches to overcome the limitations of conventional ...

Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small ...

Retrospective Comparative Analysis of Prostate Cancer In-Basket Messages: Responses From Closed-Domain Large Language Models Versus Clinical Teams.

OBJECTIVE: To evaluate the effectiveness of RadOnc-generative pretrained transformer (GPT), a GPT-4 based large language model, in assisting with in-b...

Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses.

Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and disti...

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are crit...