Orthopedics

Assessing the quality and readability of ChatGPT responses to frequently asked questions about trigger finger release.

Artificial intelligence, specifically large language models like ChatGPT, is rapidly transforming the healthcare landscape. As ChatGPT becomes more popular for obtaining medical information, there are concerns regarding the accuracy and quality of its content. While prior studies in various medical specialties have yielded mixed results regarding ChatGPT's reliability, little research has focused ...

A rule-based method to automatically locate lumbar vertebral bodies on MRI images.

BACKGROUND: Segmentation is a critical process in medical image interpretation. It is also essential for preparing training datasets for machine learning (ML)-based solutions. Despite technological advancements, achieving fully automatic segmentation is still challenging. User interaction is required to initiate the process, either by defining points or regions of interest, or by verifying and ref...

Passive ankle and hindfoot kinematics within a robot-driven tibial movement envelope.

Accurate description of individual bone kinematics is essential for understanding individual foot and ankle joint function and interactions. While inv...

The automatic pelvic screw corridor planning for intact pelvises based on deep learning deformable registration.

Percutaneous screw fixation technique in pelvic trauma surgery is an extremely challenging operation that typically requires a trial-and-error inserti...

Ensemble learning of deep CNN models and two stage level prediction of Cobb angle on surface topography in adolescents with idiopathic scoliosis.

This study employs Convolutional Neural Networks (CNNs) as feature extractors with appended regression layers for the non-invasive prediction of Cobb ...

Bridging innovation to implementation in artificial intelligence fracture detection : a commentary piece.

The deployment of AI in medical imaging, particularly in areas such as fracture detection, represents a transformative advancement in orthopaedic care...

Validation of a novel artificial intelligence model (SpinePose) to automatically and accurately predict spinopelvic parameters using scoliosis radiographs in an external cohort.

OBJECTIVE: SpinePose was developed in 2024 as a novel artificial intelligence (AI) tool to automatically predict spinopelvic parameters with high accu...

A Machine Learning Algorithm to Estimate the Probability of a True Scaphoid Fracture After Wrist Trauma.

PURPOSE: To identify predictors of a true scaphoid fracture among patients with radial wrist pain following acute trauma, train 5 machine learning (ML...

Evaluation of blood- and urine-derived biomarkers for machine learning prediction models of osteoarthritis in elderly patients: A feasibility study.

BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease, particularly affecting individuals aged >50 years. It deteriorates quality of ...

AI for fracture diagnosis in clinical practice: Four approaches to systematic AI-implementation and their impact on AI-effectiveness.

PURPOSE: Artificial Intelligence (AI) has been shown to enhance fracture-detection-accuracy, but the most effective AI-implementation in clinical prac...

Predicting strength of femora with metastatic lesions from single 2D radiographic projections using convolutional neural networks.

BACKGROUND AND OBJECTIVE: Patients with metastatic bone disease are at risk of pathological femoral fractures and may require prophylactic surgical fi...

Disc Diffusion Reader: an AI-powered potential solution to combat antibiotic resistance in developing countries.

INTRODUCTION: Antimicrobial resistance (AMR) is a global health challenge, and antimicrobial susceptibility testing (AST) is vital for guiding treatme...

PB&J: Peanut Butter and Joints for Damped Articulation

Many bioinspired robots mimic the rigid articulated joint structure of the human hand for grasping tasks, but experience high-frequency mechanical p...

Vision LLMs Are Bad at Hierarchical Visual Understanding, and LLMs Are the Bottleneck

This paper reveals that many state-of-the-art large language models (LLMs) lack hierarchical knowledge about our visual world, unaware of even well-...

Bi-Manual Joint Camera Calibration and Scene Representation

Robot manipulation, especially bimanual manipulation, often requires setting up multiple cameras on multiple robot manipulators. Before robot manipu...

Model-Guided Network with Cluster-Based Operators for Spatio-Spectral Super-Resolution

This paper addresses the problem of reconstructing a high-resolution hyperspectral image from a low-resolution multispectral observation. While spat...

Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts

Multimodal large language models (MLLMs) require a nuanced interpretation of complex image information, typically leveraging a vision encoder to per...

AMIA: Automatic Masking and Joint Intention Analysis Makes LVLMs Robust Jailbreak Defenders

We introduce AMIA, a lightweight, inference-only defense for Large Vision-Language Models (LVLMs) that (1) Automatically Masks a small set of text-i...

EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding

Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-paced, occlusion-heavy environment, necessitating ...

Three-dimensional automated segmentation of adolescent idiopathic scoliosis on computed tomography driven by deep learning: A retrospective study.

Accurate vertebrae segmentation is crucial for modern surgical technologies, and deep learning networks provide valuable tools for this task. This stu...