Orthopedics

Development and Internal Evaluation of a Deep Learning Model for Fine-Grained Detection of Dental Trauma on CBCT-Dominant Image Records.

OBJECTIVES: To develop and internally evaluate a YOLO-based model for fine-grained localization and classification of dental trauma subtypes. METHODS: This retrospective single-center study used a CBCT-dominant dataset of 1,256 annotated trauma instances (1,065 instances derived from sagittal CBCT images and 191 instances derived from periapical radiographs) to develop and internally evaluate a YO...

Dual-stage anatomical perception and reasoning framework for automated cobb angle estimation.

Accurate and automated Cobb angle measurement is essential for the diagnosis and management of Adolescent Idiopathic Scoliosis (AIS). However, existing deep learning approaches often ignore the intrinsic anatomical dependencies of the spine, which results in physiologically implausible estimations. We propose a two-stage anatomical perception and reasoning framework based on keypoint detection for...

MRI Evaluation of Axial Spondyloarthritis: From Early Diagnosis to Therapeutic Response Assessment.

Magnetic resonance imaging (MRI) has reshaped the evaluation of axial spondyloarthritis (axSpA), which comprises radiographic axSpA (historically anky...

Evaluation of Differential Diagnosis of Odontogenic Lesions in Cone Beam Computed Tomography Images Using Radiomics-Based Machine Learning.

OBJECTIVE: This study aimed to evaluate the structural characteristics of mandibular alveolar bone in patients with Type 1 diabetes mellitus (T1DM), T...

Systematic assessment of the medical utility of radiology and diagnostic Artificial Intelligence in fracture detection (SAMURAI-fracture): a protocol for a multicentre cluster-randomised controlled trial.

INTRODUCTION: Fracture misdiagnosis is a common diagnostic error in emergency departments (EDs) and minor injury units (MIUs), leading to poor patient...

Single-photon emission computed tomography/computed tomography-based radiomics of bone metastases for predicting epidermal growth factor receptor mutation status and targeted therapy efficacy in non-small-cell lung cancer.

BACKGROUND: This study aimed to develop a single-photon emission computed tomography/computed tomography (SPECT/CT)-based radiomics model using bone m...

ChatGPT as a source of surgical information: Evaluation of responses to patient questions on hallux rigidus fusion.

BACKGROUND: Patients are increasingly turning to online resources and artificial intelligence (AI)-based tools to obtain information about orthopedic ...

AI-assisted radiographic fracture detection and length of stay in the adult ambulatory orthopedic emergency department: a before-after cohort study with a disease-specific internal control.

BACKGROUND: Although artificial intelligence-assisted radiographic fracture detection tools (AI-RFDT) have demonstrated high diagnostic accuracy in ad...

Observer-Blinded Comparison of Virtual and Manual Finger ROM in AI-Based 3-Dimensional Hand Models.

PURPOSE: To examine the validity, agreement, and intra- and inter-rater reliability of an artificial intelligence (AI)-based 3-dimensional hand modeli...

Deep learning-based improvement of joint angle accuracy for uncalibrated multi-view markerless three-dimensional motion capture.

This study aimed to improve and validate the accuracy of joint angles estimated using a mixture of uncalibrated cameras (MUC), an uncalibrated multi-v...

Large Language Models in Spine Surgery: A Scoping Review of Clinical Efficacy, Technical Integration, and Ethical Paradigms.

Study DesignScoping review.ObjectivesTo map spine literature on large language models, characterize reported use cases, and identify evidence gaps lim...

Unlocking forensic potential: machine learning-driven estimation of sex, age, and stature from proximal femur using dual-energy X-ray absorptiometry.

Beyond its clinical applications, Dual-Energy X-ray Absorptiometry (DXA) offers potential for forensic biological profiling, particularly in cases inv...

Readability of AI-Generated Patient Visit Summaries in Orthopedic Surgery: Retrospective Analysis.

BACKGROUND: Patient visit summaries (PVS) are patient-facing documents intended to reinforce communication and promote patient education after clinica...

Two-stage deep learning framework for magnetic resonance imaging-based detection of temporomandibular joint osteoarthritis.

OBJECTIVES: Cone-beam computed tomography (CBCT) is the reference standard for detecting osseous changes in temporomandibular joint osteoarthritis (TM...

Information matters, but cues are dangerous: a comparative evaluation of three multimodal AI chatbots in oral and maxillofacial radiology.

OBJECTIVES: To compare the diagnostic performance of three multimodal AI chatbots on oral and maxillofacial radiographic images and to examine how add...

Biomechanics-Embedded Deep Learning for Joint Moment Estimation in Clinical Gait Analysis for Cerebral Palsy: A Learnable Hill-Type Pathway.

Accurate lower-limb joint moment estimation is essential for clinical gait analysis in children with cerebral palsy (CP), yet conventional methods req...

Toward foundation-model-assisted biomechanical simulation of the knee joint: Current evidence, limitations, and future directions.

Subject-specific finite element analysis (FEA) can estimate tissue-level stress, strain, contact pressure, and load transfer in the knee, but building...

Machine learning-based GA optimization of lumbar intervertebral disc FE models: Comparison with RSM and experimental data.

Finite element (FE) models are widely used to investigate the mechanical behaviour of the human Intervertebral Disc (IVD), but their predictive capabi...

Preserving privacy, enabling collaboration: Decentralized learning framework for multi-class orthopedic imaging.

Medical imaging data are inherently distributed across healthcare institutions and subject to strict privacy regulations, limiting the feasibility of ...

Patient-safe radiological language: Reducing nocebo harm in orthopedic imaging reports.

As patients increasingly access radiology reports through electronic portals, imaging reports are no longer private technical communications between c...