Urology

Machine learning modeling for the risk of acute kidney injury in inpatients receiving amikacin and etimicin.

BACKGROUND: Acute kidney injury (AKI) is a significant concern among hospitalized patients receiving aminoglycosides. Identifying the risk factors associated with aminoglycoside-induced AKI and developing machine learning models are imperative in clinical practice.

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 current work, we have incorporated it into the general utility lattice program (GULP) and the large-scale atomic/molecular massively parallel simulator (LAMMPS), which are programmed with modern FORTRAN and C++, respectively. The parameters of ReaxFF-nn can be trained using our I-ReaxFF package. By combin...

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 applications in urology.

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 MR images with high accuracy and generalization abi...

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 by intricate interactions between metabolic reprogr...

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 online content quality varies widely. This study ai...

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 research has highlighted acute kidney injury (AKI) that ...

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 detecting bone metastases in prostate cancer (PCa). Ho...

Promoting patient health literacy in burn care through artificial intelligence language learning models: A study of text analysis and simplification.

Health literacy is essential in patient care, especially in burn treatment, where understanding care information can significantly influence recovery ...

Challenges and Opportunities: Interplay between Infectious Disease and Antimicrobial Resistance in Medical Device Surface Applications.

Antimicrobial resistance (AMR) is a growing silent pandemic driven by multidrug-resistant infections, particularly those associated with medical devic...

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

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 image segmentation and provide workflow assistance...

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 mortality. It is the most common type of cancer i...

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 in the non-invasive assessment of coronary artery d...

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 malignancy and is the second most common male cancer in the...

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 multi-center datasets for improved generalizability; ...

Portable Ultrasound Bladder Volume Measurement Over Entire Volume Range Using a Deep Learning Artificial Intelligence Model in a Selected Cohort: A Proof of Principle Study.

OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) i...

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

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, significantly affecting patients' quality of life. T...

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 specific location of deposits within glomeruli. M...