Orthopedics

Automated data extraction for systematic reviews using GPT-5.2 and Google Gemini Pro 3: A dual-large language model approach in orthopaedic research.

PURPOSE: To evaluate the accuracy, agreement, and efficiency of a dual-large language model (LLM) approach using Generative Pre-Trained Transformer 5.2 (GPT-5.2) and Google Gemini 3 Pro for automated data extraction in orthopaedic systematic reviews. METHODS: Eight studies from a previously published systematic review on paediatric revision anterior cruciate ligament reconstruction were used to te...

Robotic-assisted and AI-augmented arthroplasty: converging technologies in joint replacement.

SuperLearner approach for predicting imminent risk of fracture in older Chinese patients with newly diagnosed osteoporosis based on their routine blood test markers.

Single-cell co-mapping reveals relationship between chromatin state and gene expression in early zebrafish development.

Establishing a cell type-specific chromatin landscape is crucial for the maintenance of cell identity during embryonic development. However, our knowl...

autoscoRA: Deep Learning to Automate Sharp/van der Heijde Scoring of Radiographic Damage in Rheumatoid Arthritis.

OBJECTIVE: Regular imaging by conventional radiography to assess for joint damage is a cornerstone in the management of rheumatoid arthritis (RA). Sco...

High-resolution deep learning DIXON MRI of the sacroiliac joints is non-inferior to standard MRI in patients with suspected axial Spondyloarthritis.

OBJECTIVE: To compare the standard multi-sequence MRI protocol (sMRI) of the sacroiliac joints with a single high-resolution deep learning-reconstruct...

Generative artificial intelligence for surgical site infection surveillance.

BACKGROUND: Surgical site infection (SSI) surveillance can be time consuming and resource intensive. This study investigates the potential of generati...

Identification of Autophagy-related Genes of the Osteoarthritis Using Machine Learning Algorithm.

Exploring Patient Perspectives on the Use of Artificial Intelligence to Inform Joint Decision-Making for Patients With Multiple Conditions in Primary Care in the United Kingdom: Qualitative Study.

BACKGROUND: Multimorbidity, living with 2 or more long-term health conditions, is increasing globally and now affects over one-quarter of adults in En...

IPEM Topical Report: A National Survey of MRI Use for External Beam Radiotherapy Treatment Planning in the UK: 2025 IPEM Survey Results.

Magnetic Resonance Imaging (MRI) offers superior soft tissue contrast compared to Computed Tomography (CT), making it highly valuable in external beam...

Accurate classification and prediction of knee osteoarthritis based on Al-Biruni Earth Radius metaheuristic optimizer and LSTM classifier.

Controlled comparative study of YOLOv8-Pose, YOLOv11-Pose, and Detectron2 for vertebrae detection and keypoint estimation.

Accurate vertebrae detection with precise keypoint localization is essential for medical image analysis and clinical applications, such as spinal alig...

Artificial Intelligence-assisted Periapical Radiographic Assessment: Lesion Detection, Endodontic Complication Analysis, and Review of Clinical Treatment Recommendations.

INTRODUCTION: Artificial intelligence (AI) systems are increasingly used in dental radiology to support endodontic diagnosis. However, their diagnosti...

Electrophysiologically informed spiking neural networks for fish-inspired navigation with boundary vector cells and hydrostatic pressure cues.

Spatial memory is a fundamental cognitive capacity governing the mental encoding of spatial information, which can be used to navigate through intrica...

Accuracy in spinal level determination, including transitional vertebrae: an ASReview supported systematic review.

Lumbar Spine Disorder Detection using Segmentation and IBN-MGNet Classification with Enhanced Feature Extraction.

Back pain affects millions worldwide, with lumbar spine disorders (LSDs) being a major contributing factor due to the spine's critical role in support...

The effect of an artificial intelligence-assisted motivational procedure on kinesiophobia and mobility after total knee arthroplasty: a randomized controlled trial.

Development and Validation of a Machine Learning Model for Predicting Postoperative Delirium in Elderly Patients with Hip Fracture: A Retrospective Cohort Study.

Postoperative delirium (POD) is a common and serious complication in elderly hip fracture patients, including those undergoing surgery for femoral nec...

Development of Novel and Interpretable Automated Models for Predicting Total Knee Replacement in Knee Osteoarthritis: An International Multicenter Study.

RATIONALE AND OBJECTIVES: Subtle changes in the infrapatellar fat pad (IPFP) enable prediction and quantification of knee osteoarthritis (KOA). This s...

Patient specific optimization and planning of vertebral augmentation in osteoporosis: Finite element and Artificial Intelligence approaches.

BACKGROUND: Osteoporotic Vertebral Compression Fractures (OVCFs) are responsible for significant disability, especially among individuals with low Bon...