Surgery

Evaluating the quality, understandability, actionability, and readability of ChatGPT-generated patient information on overactive bladder: A cross-sectional study.

This cross-sectional study aimed to evaluate the quality, understandability, actionability, and readability of patient-oriented information generated by ChatGPT regarding overactive bladder (OAB). A total of 32 frequently asked patient questions related to OAB were categorized into 6 domains, including general information, diagnosis, lifestyle and behavioral management, medical treatment, minimall...

The Science of Preventing Delirium: Trends, Knowledge Gaps, and Future Directions Revealed Through Bibliometric Insights.

PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development and emerging directions. DESIGN: A bibliometric analysis. METHODS: Data were retrieved from the Web of Science Core Collection, focusing on publications between January 1, 2015, and December 31, 2024. The analysis utilized VOSviewer, CiteSpace, and ...

Real-world multimetric comparison of four commercial artificial intelligence solutions for intracranial hemorrhage detection.

PURPOSE: To evaluate the real-world multimetric performance of four commercially available computed tomography (CT)-based artificial intelligence (AI)...

Computer-Vision Approach to Triaging Patient-Submitted Photos of Intestinal Ostomies.

BACKGROUND: Surgeons and ostomy nurses receive a high volume of stoma photos from patients. OBJECTIVE: This study aimed to develop and validate an aut...

Automated early preterm detection using hybrid multimodal attention network with gated fusion.

Preterm birth is a major pregnancy complication associated with increased maternal and neonatal risks, making early detection of labor essential. Elec...

Spatial architecture of tertiary lymphoid structures represents an independent prognostic dimension in hepatocellular carcinoma.

BACKGROUND AND AIMS: Tertiary lymphoid structures (TLS) are associated with heterogeneous outcomes in hepatocellular carcinoma (HCC), but whether thei...

Deep learning-based automatic measurement of spinal alignment and implant detection in scoliosis radiographs.

Deep learning-based automated analysis offers the potential to streamline workflows, improve reproducibility, and reduce clinician workload. We develo...

Neoadjuvant Chemoradiotherapy on Postoperative Complications of Rectal Cancer: A Retrospective Study Integrating MRI Radiomics and Deep Learning.

Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer but increases postoperative complication (POC) risks due to tissue...

Improving Surgical Scheduling Efficiency with Operating Room Coordination and Allocation at Centre Antoine Lacassagne: A Comparative Analysis of Patient Outcomes and Operational Metrics.

BACKGROUND: Operating room (OR) scheduling is critical for timely patient care, optimal resource usage, and equitable surgical access. Despite the cos...

Data-centric physics-inspired deep learning framework for saturation artifact removal in optical coherence tomography.

In Fourier-domain optical coherence tomography (FD-OCT) imaging, saturation of the data acquisition chain leads to loss of information by clipping the...

Development and validation of a routine blood test-based model to predict in-hospital postoperative pulmonary infection in older patients with hip fracture.

BACKGROUND: Postoperative pulmonary infection (PPI) is a common and serious complication in older adults undergoing hip fracture surgery, leading to p...

Den-SOFA: Dental Student Outcome Forecasting Assistant using explainable machine learning models.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are increasingly being explored in dental education to support academic assessment ...

Patient and physician perspectives on large language model generated responses about brain aneurysm.

PURPOSE: Large language models (LLMs) are becoming increasingly popular in medicine and neurosurgery. Because LLMs are not trained in specific subspec...

Machine learning-based prediction of hospital-associated complications after tibial fracture surgery in older patients: a nationwide Japanese database study.

BACKGROUND: Older adults requiring emergency surgery for acute tibial fractures are vulnerable to hospital-associated complications (HACs), but admiss...

Noninvasive Preoperative Evaluation in Drug-Resistant Epilepsy Based on the Brain Network Topological Dynamics.

Drug-resistant epilepsy (DRE) affects over 50 million individuals worldwide, yet surgical resection, the most effective treatment, achieves seizure fr...

Publicly Accessible Large Language Model Responses to Frequently Asked Questions About Spondylodiscitis: Preliminary Expert Evaluation.

BACKGROUND: Patients increasingly use large language models (LLMs) to obtain medical information, but the quality of LLM-generated information on comp...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...

The Rise of AI Companions: From Prediction to Surgery in the Digital Twin Era.

Artificial intelligence (AI) is rapidly reshaping orthopaedic surgery, supported by advances in data science, computational power, and perioperative d...

Development of Convolutional Neural Networks for Classification and Characterisation of Proximal Humerus Fractures on Computed Tomography.

BACKGROUND: Agreement between surgeons on classification, characterization and choice of treatment for proximal humerus fractures (PHFs) is poor, lead...

Diagnostic Performance of Deep Learning for Automated Mandibular Canal Segmentation on CBCT Images: A Systematic Review and Meta-Analysis.

INTRODUCTION: Accurate localization of the mandibular canal in Cone-Beam Computed Tomography (CBCT) images is critical for preventing iatrogenic nerve...