Urology

Synthesizing [F]PSMA-1007 PET bone images from CT images with GAN for early detection of prostate cancer bone metastases: a pilot validation study.

BACKGROUND: [F]FDG PET/CT scan combined with [F]PSMA-1007 PET/CT scan is commonly conducted for dete...

A Machine Learning Method for Predicting Acute Kidney Injury in Patients with Intracranial Hemorrhage.

Intracranial hemorrhage (ICH) is a critical and urgent condition in clinical practice. Recent resear...

Assessing the quality of Japanese online breast cancer treatment information using large language models: a comparison of ChatGPT, Claude, and expert evaluations.

BACKGROUND: The internet is a primary source of health information for breast cancer patients, but o...

Metabolic reprogramming and immune microenvironment profiling in clear cell renal cell carcinoma: implications for prognosis, targeted therapy, and drug resistance.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of kidney cancer, distinguished b...

Deep Learning with Domain Randomization in Image and Feature Spaces for Abdominal Multiorgan Segmentation on CT and MRI Scans.

Purpose To develop a deep learning segmentation model that can segment abdominal organs on CT and M...

Current application of blockchain technology in healthcare and its potential roles in Urology.

OBJECTIVE: To assess the current uses of blockchain technology in surgery and explore potential appl...

ReaxFF-nn: a reactive machine-learning potential in GULP/LAMMPS and its applications in the thermal conductivity calculations of carbon nanostructures.

The term "ReaxFF-nn" refers to the reactive force field (ReaxFF) with neural networks. In the curren...

Trading off Iodine and Radiation Dose in Coronary Computed Tomography.

Coronary CT angiography (CCTA) has seen steady progress since its inception, becoming a key player i...

Histopathology-Based Prostate Cancer Classification Using ResNet: A Comprehensive Deep Learning Analysis.

Prostate cancer is the most prevalent solid tumor in males and one of the most common causes of male...

Challenges in Using Deep Neural Networks Across Multiple Readers in Delineating Prostate Gland Anatomy.

Deep learning methods provide enormous promise in automating manually intense tasks such as medical ...

A pilot study using ambient artificial intelligence scribes in clinical documentation in a urology outpatient clinic.

Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.

INTRODUCTION: Prostate adenocarcinoma (PRAD) is an extremely widespread site of urological malignanc...

Combining Clinical, Genetic and Protein Markers Using Machine Learning Models Discriminates Psoriatic Arthritis Patients From Those With Psoriasis.

BACKGROUND: Psoriatic Arthritis (PsA), an immune mediated inflammatory arthritis, affects a quarter ...

Identification of a panel of volatile organic compounds in urine for early detection of for bladder cancer.

The absence of specific markers makes early detection of bladder cancer (BC) challenging. Recent stu...

Utilizing Deep Learning to Identify Electron-Dense Deposits in Renal Biopsy Electron Microscopy Images.

INTRODUCTION: Electron microscopy (EM) is a crucial technique for identifying and distinguishing the...

XGBoost model for predicting erectile dysfunction risk after radical prostatectomy: development and validation using machine learning.

BACKGROUND: Erectile dysfunction (ED) is a frequent complication following radical prostatectomy, si...

Bridging the gap: the role of large language model refinement in readability in urology research.

Federated Learning for Renal Tumor Segmentation and Classification on Multi-Center MRI Dataset.

BACKGROUND: Deep learning (DL) models for accurate renal tumor characterization may benefit from mul...

Natural products in treating diabetic kidney disease: a visualized bibliometric analysis.

BACKGROUND: Diabetic kidney disease (DKD) is one of the most significant complications in diabetic p...

VADEr: Vision Transformer-Inspired Framework for Polygenic Risk Reveals Underlying Genetic Heterogeneity in Prostate Cancer.

Polygenic risk scores (PRSs) serve as quantitative metrics of genetic liability for various conditio...

Machine Learning-based Dose Prediction in [Lu]Lu-PSMA-617 Therapy by Integrating Biomarkers and Radiomic Features from [Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography.

PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorb...