Orthopedics

Comparative Evaluation of ChatGPT-4o and Grok-3 on Cleft Lip and Palate and Presurgical Infant Orthopedics: A Multidisciplinary Assessment by Orthodontists, Pediatricians, and Plastic Surgeons.

Objective: This study aimed to evaluate and compare the accuracy, clarity, and clinical applicability of 2 state-of-the-art large language models (LLMs), Chat Generative Pretrained Transformer (ChatGPT)-4o and Grok-3, in generating health information related to cleft lip and palate (CLP) and presurgical infant orthopedics (PSIO). To ensure a multidisciplinary perspective, experts from orthodontics...

Single Port Robot-Assisted Supraclavicular Flap Repair of Iatrogenic Hardware-Associated Pharyngeal Perforation: A Case Report.

BACKGROUND: The incidence of iatrogenic pharyngeal perforation has been reported to comprise 50%-75% of all pharyngeal perforations. In the context of anterior cervical diskectomy and fusion (ACDF) procedures, pharyngeal perforations are a known, although rare, complication with a morbidity and mortality rate of 4%. METHODS: In the following case report, we describe a 19-year-old male who underwen...

Harnessing Artificial Intelligence for Shoulder Ultrasonography: A Narrative Review.

Shoulder pain is a common musculoskeletal complaint requiring accurate imaging for diagnosis and management. Ultrasound is favored for its accessibili...

Deep-Learning System for Automatic Measurement of the Femorotibial Rotational Angle on Lower-Extremity Computed Tomography.

To develop and validate a deep-learning-based algorithm for automatic identification of anatomical landmarks and calculating femoral and tibial versio...

Letter to the editor regarding Ritter et al: "Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty".

Response to Baek et al. regarding: "Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty".

Assessing the ability of large language models to simplify lumbar spine imaging reports into patient-facing text: a pilot study of GPT-4.

OBJECTIVE: To assess the ability of large language models (LLMs) to accurately simplify lumbar spine magnetic resonance imaging (MRI) reports. MATERIA...

Expandable, But at What Cost? Failure Patterns in Corpectomy Cages From 373 Real-World Adverse Events.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study aimed to analyze the failure patterns of expandable corpectomy cages. SUMMARY OF BACKGROUND...

Utility of Multiclass Machine Learning Algorithms in Predicting Same-Day Discharge Following Primary Total Knee Arthroplasty.

BACKGROUND: Length of stay (LOS) is a substantial driver of costs following primary total knee arthroplasty (TKA), leading to increased efforts target...

Comparative Evaluation of Deep Learning and Foundation Model Embeddings for Osteoarthritis Feature Classification in Knee Radiographs.

Foundation models (FM) offer a promising alternative to supervised deep learning (DL) by enabling greater flexibility and generalizability without rel...

Deep learning for automated 3D assessment of rotator cuff muscle atrophy and fat infiltration prior to total shoulder arthroplasty.

BACKGROUND: Rotator cuff muscle pathology affects outcomes following total shoulder arthroplasty, yet current assessment methods lack reliability in q...

From algorithms to answers: a comparative analysis of popular search engines and large language models on clubfoot patient education.

This study evaluates Chat Generative Pre-Trained Transformer 4o's (ChatGPT-4o's) utility in clinical relevance and accuracy compared with Google for p...

Predictive Value of Geriatric Nutritional Risk Index and Risk Analysis Index for Post-operative Outcomes in Spine Surgery Patients: A Comprehensive Analysis.

Study DesignRetrospective cohort study.ObjectivesFrailty and nutritional status are predictors of adverse spine surgery outcomes. This study evaluated...

Deep Learning-Based Detection of Papilledema on Retinal Photographs From Handheld Cameras: A Prospective Study.

BACKGROUND: Papilledema and other optic neuropathies are critical findings in neuro-ophthalmology that require timely and accurate diagnosis. This stu...

Deep Learning-Based 3D and 2D Approaches for Skeletal Muscle Segmentation on Low-Dose CT Images.

Automated segmentation of skeletal muscle from computed tomography (CT) images is essential for large-scale quantitative body composition analysis. Ho...

Assessment of Multimodal Natural Language Processing in Ascertaining Perioperative Safety Indicators From Preoperative Notes in Spine Surgery.

INTRODUCTION: Standard spine surgery machine learning (ML) models often rely on structured clinical data, overlooking nuanced free text, such as preop...

Big Data in Neurosurgery: A Guideline on Data Structures, Machine Learning Models, and Ethical Considerations.

Artificial intelligence (AI) is reshaping neurosurgery, offering unprecedented opportunities to enhance diagnostics, personalize treatment, and predic...

Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review.

OBJECTIVES: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizi...

A scoping review on emerging technologies and automation of musculoskeletal ergonomic assessments.

Ergonomic suitability is critical in tasks involving musculoskeletal movement. Many industries have examined best practices and assessed workers' ergo...

A Deep Learning Tool for Hip Minimum Joint Space Width Calculation on Antero-posterior Pelvis Radiographs.

BACKGROUND: Minimum joint space width (mJSW) is a useful quantitative metric of osteoarthritis progression in the hip, particularly as a continuous va...