Orthopedics

Dynamic prediction of paroxysmal atrial fibrillation onset using longitudinal sample entropy in joint models.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with a five-fold increased risk of stroke. Early prediction of AF onset could improve care for at-risk patients. Existing predictive models often rely on clinical risk scores or machine learning approaches using, for instance, heart rate variability (HRV) features. Among these, sample entropy (SampEn), a q...

Deep learning model for identification of metabolic bone disease of prematurity using wrist radiographs.

This study proposes a wrist radiography-based deep learning model for identifying radiographic features of metabolic bone disease (MBD) of prematurity and evaluate the impact of its decision support. This retrospective study included preterm infants with birth weights under 1500 g, born at Seoul National University Hospital (internal dataset: 814 subjects) and Seoul National University Bundang Hos...

Unraveling the Mechanistic Spectrum of Myhre Syndrome: SMAD4 Signaling Disruption, Skeletal Phenotypes, and Translational Innovation.

Myhre syndrome (MYHRS) is an ultra-rare, progressive multisystem disorder caused by recurrent heterozygous missense variants in the SMAD4 gene, a cent...

TFAP2A transcriptionally regulates B3GALT2 to affect gouty arthritis progression through pyroptosis: a study based on machine learning and multi-omics integration analysis.

BACKGROUND: Gouty arthritis (GA) is an inflammatory joint disease driven by monosodium urate (MSU) crystal deposition. The NOD-like receptor thermal p...

Advances in β-titanium alloys for safer and greener biomedical implants.

In the biomedical field, titanium alloys have long been preferred for orthopedic and dental devices due to their excellent biocompatibility and mechan...

BackTracker: Machine learning to identify kinematic phenotypes for personalised exercise management in non-specific low back pain.

BACKGROUND: Low back pain (LBP) is a leading cause of global disability. Most cases are non-specific (NSLBP) and lack identifiable causes. Early activ...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

CT- DImQ: An open-access platform for image quality assessment of CT systems- application to CT values and noise characterization in 3D-printed anthropomorphic thorax phantoms.

PURPOSE: To present an open access platform for CT image quality assessment combined with anthropomorphic phantoms. To promote the accessibility of an...

AI-driven 3D virtual surgical planning in total hip arthroplasty: a machine learning approach for precision implant positioning and improved clinical outcomes.

PURPOSE: To explore the clinical significance of the artificial intelligence (AI)-assisted three-dimensional (3D) planning system AI-HIP in total hip ...

Artificial intelligence for fracture detection on computed tomography: a comprehensive systematic review and meta-analysis of diagnostic test accuracy in non-commercial and commercial solutions.

Rising patient volumes, the increasing use of computed tomography (CT) imaging in emergency departments and the resulting prolonged waiting times high...

An improved activation function for the recognition of knee osteoarthritis severity.

BACKGROUND: Existing knee osteoarthritis (KOA) severity classification methods typically rely on a combination of object detection algorithms and clas...

Real-world use of PACS-integrated automated spine numbering in MRI.

PURPOSE: Traditional methods of vertebral identification have predominantly relied on relative approaches, depending on discernible landmarks. Artific...

Artificial intelligence in virtual fracture clinics: a systematic review of imaging and clinical-text tools.

BACKGROUND: Virtual fracture clinics (VFCs) are a well-established component of acute orthopedic management pathways. Artificial intelligence (AI) hea...

Prediction of skeletal maturity using machine learning based on multiple biological indicators.

INTRODUCTION: Accurate assessment of skeletal maturity is essential for orthodontic treatment planning and growth modulation. This study aimed to deve...

The Evolving Role of Musculoskeletal Ultrasound in Gout: From Diagnosis to Management-A Narrative Review.

Gout, a prevalent and treatable form of crystal-induced arthritis, results from monosodium urate (MSU) crystal deposition in articular and periarticul...

Machine learning model identifies tibial anatomical variables as potential risk factors for anterior cruciate ligament injury.

PURPOSE: The tibial slope is a well-known risk factor for anterior cruciate ligament (ACL) injury. As machine learning continues to progress, it has b...

Opportunistic osteoporosis screening using CT-based Hounsfield units: a machine learning approach for preoperative spine surgery planning.

Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study.

BACKGROUND: General anesthesia comprises 3 essential components-hypnosis, analgesia, and immobility. Among these, maintaining an appropriate hypnotic ...

Non-coding RNAs as prognostic biomarkers in autoimmune disease.

Autoimmune diseases comprise a broad spectrum of disorders in which both the innate and adaptive branches of the immune system malfunction, mistakenly...

Open-Source Machine Learning Computed Tomography Scan Segmentation for Spine Osteoporosis Diagnostics.

BACKGROUND AND OBJECTIVES: Dual-energy x-ray absorptiometry (DXA) is the standard for assessing bone mineral density (BMD); however, its accuracy is l...