Orthopedics

Machine Learning-Based Predictive Models for 90-Day Readmission of Total Joint Arthroplasty Using Comprehensive Electronic Health Records and Patient-Reported Outcome Measures.

BACKGROUND: The Centers for Medicare & Medicaid Services currently incentivizes hospitals to reduce postdischarge adverse events such as unplanned hospital readmissions for patients who underwent total joint arthroplasty (TJA). This study aimed to predict 90-day TJA readmissions from our comprehensive electronic health record data and routinely collected patient-reported outcome measures.

Utility of Artificial Intelligence in Orthopedic Surgery Literature Review: A Comparative Pilot Study.

OBJECTIVE: Literature reviews are essential to the scientific process and allow clinician researchers to advance general knowledge. The purpose of this study was to evaluate if the artificial intelligence (AI) programs ChatGPT and Perplexity.AI can perform an orthopedic surgery literature review.

Application of Artificial Intelligence at All Stages of Bone Tissue Engineering.

The development of artificial intelligence (AI) has revolutionized medical care in recent years and plays a vital role in a number of areas, such as d...

Incidence and Risk Factors for Hyponatremia in Postoperative Spinal Surgery Patients.

INTRODUCTION: The incidence of hyponatremia after orthopedic surgery is high. Hyponatremia may prolong hospitalization and increase mortality, but few...

The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review.

Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), h...

Sex estimation from the hyoid bone measurements in an adult Eastern Turkish population using 3D CT images, discriminant function analysis, support vector machines, and artificial neural networks☆.

The hyoid bone is one of the bones in the human body that shows sexual dimorphism. The anthropological and anthropometric characteristics that determi...

Synthetic Knee MRI T Maps as an Avenue for Clinical Translation of Quantitative Osteoarthritis Biomarkers.

A 2D U-Net was trained to generate synthetic T maps from T maps for knee MRI to explore the feasibility of domain adaptation for enriching existing da...

Sonographically-navigated frozen shoulder release (S-FSR): A modified technique for sonographically-navigated, in-office hydrodilatation of adhesive capsulitis.

We describe a new technique for hydrodilatation of the frozen shoulder, which we coined 'Sonographically-Navigated Frozen Shoulder Release (S-FSR)' or...

Keyhole Fenestration for Cerebrospinal Fluid Leaks in the Thoracic Spine: Quantification of Bone Removal and Microsurgical Anatomy.

BACKGROUND AND OBJECTIVE: A safe working trajectory is mandatory for spinal pathologies, especially in the midline, anterior to the spinal cord. For t...

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from pot...

Artificial intelligence-enabled ophthalmoscopy for papilledema: a systematic review protocol.

Papilledema is a pathology delineated by the swelling of the optic disc secondary to raised intracranial pressure (ICP). Diagnosis by ophthalmoscopy c...

The gait1415+2 OpenSim musculoskeletal model of transfemoral amputees with a generic bone-anchored prosthesis.

This short communication presents the gait1415+2 musculoskeletal model, that has been developed in OpenSim to describe the lower-extremity of a human ...

Automatic detection, segmentation, and classification of primary bone tumors and bone infections using an ensemble multi-task deep learning framework on multi-parametric MRIs: a multi-center study.

OBJECTIVES: To develop an ensemble multi-task deep learning (DL) framework for automatic and simultaneous detection, segmentation, and classification ...

Digital Phenotyping, Wearables, and Outcomes.

There is a significant need for robust and objective outcome assessments in spine surgery. Constant monitoring via smartphones and wearable devices ha...

Ensemble deep-learning networks for automated osteoarthritis grading in knee X-ray images.

The Kellgren-Lawrence (KL) grading system is a scoring system for classifying the severity of knee osteoarthritis using X-ray images, and it is the st...

Editorial: Clinical Integration of Artificial Intelligence in Spine Surgery: Stepping in a new Frontier.

Development and optimization of AI algorithms for wrist fracture detection in children using a freely available dataset.

INTRODUCTION: In the field of pediatric trauma computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems have emerged offering a pro...

Machine learning models with time-series clinical features to predict radiographic progression in patients with ankylosing spondylitis.

OBJECTIVE: Ankylosing spondylitis (AS) is chronic inflammatory arthritis causing structural damage and radiographic progression to the spine due to re...

Machine learning and deep neural network-based learning in osteoarthritis knee.

Osteoarthritis (OA) of the knee joint is considered the commonest musculoskeletal condition leading to marked disability for patients residing in vari...

A method of bedside urethrography before catheterization in pelvic trauma in Korea: a case report.

We introduce a convenient method of urethrography before catheterization for patients with pelvic trauma that can be used in a resuscitation area. A 1...