Orthopedics

An online non-radiographic osteoporosis prediction calculator constructed using interpretable machine learning.

Is the Google Artificial Intelligence Overview Accurate for Current Procedural Terminology Coding in Hand Surgical Procedures?

PURPOSE: As the Google Artificial Intelligence (AI) Overview function becomes engrained in the search engine, it is important to understand the accuracy of these search results as they pertain to Current Procedural Terminology (CPT) codes. We hypothesized that the identified codes will not be 100% accurate and that there will be subgroups of procedures with relatively lower accuracy than others. M...

Plasma Proteomic Profiling Identifies a Six-Protein Panel for Grading and Predicting Intervertebral Disc Degeneration.

Intervertebral disc degeneration (IDD) represents a significant health concern affecting a large portion of the population and leads to chronic pain a...

Bioinspired growable humanoid robot with bone-mimetic linkages for versatile mobility.

Inspired by human biomechanics, humanoid robots are often designed to mimic human kinematics but typically lack key traits of developing bones, such a...

Smart scheduling of arthroplasty surgery with machine learning and optimisation improves operating room utilisation.

OBJECTIVES: Total hip and knee arthroplasty (THA and TKA, respectively) are effective procedures but are costly and resource intensive. As such, sched...

Osteoarthritis year in review 2025: Biomechanics.

OBJECTIVE: Biomechanical loading is a known contributor to osteoarthritis (OA) pathogenesis, and one of the few modifiable risk factors. Thus, researc...

Full-Endoscopic Spine Surgery for Adjacent Segment Disease Using Artificial Intelligence-Assisted 3-Dimensional MRI/CT Fusion Imaging: A Case Report.

CASE: An 82-year-old woman presented with right medial thigh pain. Her medical history included multiple lumbar decompression and fusion surgeries. Sh...

Channel-wise joint disentanglement representation learning for B-mode and super-resolution ultrasound based CAD of breast cancer.

B-mode ultrasound (BUS) is widely used in breast cancer diagnosis, while the emerging super-resolution ultrasound (SRUS) provides microvascular inform...

A review of current applications of photon-counting CT in musculoskeletal imaging.

Photon-counting computed tomography (PCCT) is a significant technological advancement in musculoskeletal imaging. Unlike traditional CT detectors, whi...

AI-based prediction of best-corrected visual acuity in patients with multiple retinal diseases using multimodal medical imaging.

BACKGROUND/AIMS: This study evaluated the performance of artificial intelligence (AI) algorithms in predicting best-corrected visual acuity (BCVA) for...

Breaking the performance barrier in deep learning-based SSVEP-BCIs: a joint frequency-phase training strategy.

Objective.Deep learning (DL) exhibits considerable potential for steady-state visual evoked potential (SSVEP) classification in electroencephalography...

MMoGCN: a multi-gate mixture of graph convolutional network model for EEG emotion and mood disorder recognition.

Objective.Emotional states and mood disorders are closely interconnected, and their joint recognition serves as a critical pathway to uncovering their...

Fully automatic AI diagnosis of alveolar bone defect in anterior teeth on CBCT images.

OBJECTIVE: To develop a fully automatic artificial intelligence (AI) system for diagnosing alveolar bone defects (ABDs) in anterior teeth on cone-beam...

Effects of Image Degradation on Deep Neural Network Classification of Scaphoid Fracture Radiographs: Comparison Study of Different Noise Types.

BACKGROUND: Deep learning models have shown strong potential for automated fracture detection in medical images. However, their robustness under varyi...

Integrative multi-omics and machine learning framework identifies PRDX4 as a redox-EMT regulator and predictive marker in bone-metastatic breast cancer.

Bone metastasis is a major cause of morbidity and mortality in breast cancer, yet effective prognostic models and targeted therapies remain limited. H...

Clinical evaluation and bone loss prediction of titanium-zirconium implants: A retrospective study of 1-5-year follow-up.

OBJECTIVES: To evaluate the clinical and radiographic outcomes of titanium-zirconium implants, identify risk factors and develop predictive models for...

Prospective evaluation of artificial intelligence (AI) in lumbar spine magnetic resonance imaging (MRI) workflow: from deep learning (DL)-enhanced accelerated acquisition to simultaneous vision-language model (VLM)-based automated report generation.

OBJECTIVES: To evaluate the diagnostic interchangeability of DL-enhanced accelerated lumbar (L)-spine magnetic resonance imaging (MRI) with convention...

Diagnostic Accuracy of Deep Learning Models in Detecting Peri-Implant Marginal Bone Loss: A Systematic Review and Meta-Analysis.

BACKGROUND: Peri-implantitis is a common implant complication requiring early detection to prevent bone loss and implant failure. Deep learning models...

Clinical and economic impact of deep learning-enhanced opportunistic osteoporosis screening using chest radiographs with and without the osteoporosis self-assessment tool for Asians (OSTA).

UNLABELLED: Opportunistic analysis of chest radiographs with deep learning detects osteoporosis cost-effectively in women aged ≥ 50 years in Singapore...

[Artificial intelligence in spinal surgery: current applications and future perspectives].

BACKGROUND: Spinal surgery is a highly complex field increasingly shaped by digital innovation. Artificial intelligence (AI) and machine learning (ML)...