Orthopedics

OBD-Finder: Explainable Coarse-to-Fine Text-Centric Oracle Bone Duplicates Discovery

Oracle Bone Inscription (OBI) is the earliest systematic writing system in China, while the identification of Oracle Bone (OB) duplicates is a fundamental issue in OBI research. In this work, we design a progressive OB duplicate discovery framework that combines unsupervised low-level keypoints matching with high-level text-centric content-based matching to refine and rank the candidate OB dupli...

Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift

In regions lacking medically certified causes of death, verbal autopsy (VA) is a critical and widely used tool to ascertain the cause of death through interviews with caregivers. Data collected by VAs are often analyzed using probabilistic algorithms. The performance of these algorithms often degrades due to distributional shift across populations. Most existing VA algorithms rely on centralized...

Monitoring morphometric drift in lifelong learning segmentation of the spinal cord

Morphometric measures derived from spinal cord segmentations can serve as diagnostic and prognostic biomarkers in neurological diseases and injuries...

Fusing Foveal Fixations Using Linear Retinal Transformations and Bayesian Experimental Design

Humans (and many vertebrates) face the problem of fusing together multiple fixations of a scene in order to obtain a representation of the whole, wh...

Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders

Multimodal learning with variational autoencoders (VAEs) requires estimating joint distributions to evaluate the evidence lower bound (ELBO). Curren...

Accuracy of Low-Dose Chest CT-Based Artificial Intelligence Models in Osteoporosis Detection: A Systematic Review and Meta-analysis.

The purpose of this study is to systematically review and evaluate the accuracy of low-dose chest CT-based artificial intelligence in osteoporosis scr...

JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers

We present JointDiT, a diffusion transformer that models the joint distribution of RGB and depth. By leveraging the architectural benefit and outsta...

Machine Learning Meets Transparency in Osteoporosis Risk Assessment: A Comparative Study of ML and Explainability Analysis

The present research tackles the difficulty of predicting osteoporosis risk via machine learning (ML) approaches, emphasizing the use of explainable...

Probability Score for the Diagnosis of Periprosthetic Joint Infection: Development and Validation of a Practical Multi-analyte Machine Learning Model.

Background and objective The diagnosis of periprosthetic joint infection (PJI) relies on established criteria-based systems requiring interpretation a...

Deep Learning Study of Alkaptonuria Spinal Disease Assesses Global and Regional Severity and Detects Occult Treatment Status.

Deep learning (DL) is increasingly used to analyze medical imaging, but is less refined for rare conditions, which require novel pre-processing and an...

Artificial intelligence assistance using deep metric learning vs. object detection in classifying lumbar disc degeneration on magnetic resonance images.

UNLABELLED: OBJECTIVE: This study aimed to assess the performance of an image retrieval system based on the deep metric learning (DML) approach in dis...

Incorporating computer vision on smart phone photographs into screening for inflammatory arthritis: results from an Indian patient cohort.

OBJECTIVES: Convolutional neural networks (CNNs) are increasingly used to classify medical images, but few studies utilize smartphone photographs. The...

Advancing periodontal diagnosis: harnessing advanced artificial intelligence for patterns of periodontal bone loss in cone-beam computed tomography.

OBJECTIVES: The current study aimed to automatically detect tooth presence, tooth numbering, and types of periodontal bone defects from cone-beam CT (...

Deep learning image enhancement for confident diagnosis of TMJ osteoarthritis in zero-TE MR imaging.

OBJECTIVES: This study aimed to evaluate the effectiveness of deep learning method for denoising and artefact reduction (AR) in zero echo time MRI (ZT...

[Applications and prospects of artificial intelligence in cervical spine surgery].

Artificial intelligence(AI) is increasingly being utilized in the research of cervical spine diseases, encompassing areas such as image analysis, assi...

Enhancing bone metastasis prediction in prostate cancer using quantitative mpMRI features, ISUP grade and PSA density: a machine learning approach.

PURPOSE: Bone metastasis is a critical complication in prostate cancer, significantly impacting patient prognosis and quality of life. This study aims...

Feasibility of deep learning algorithm in diagnosing lumbar central canal stenosis using abdominal CT.

OBJECTIVE: To develop a deep learning algorithm for diagnosing lumbar central canal stenosis (LCCS) using abdominal CT (ACT) and lumbar spine CT (LCT)...

Artificial Intelligence Promotes the Dunning Kruger Effect: Evaluating ChatGPT Answers to Frequently Asked Questions About Adolescent Idiopathic Scoliosis.

INTRODUCTION: Patients have long turned to the Internet for answers to common medical questions. As the ability to access information evolves beyond s...

Artificial Intelligence in Spine Imaging: A Paradigm Shift in Diagnosis and Care.

Recent advancements in artificial intelligence (AI) can significantly improve radiologists' workflow, improving efficiency and diagnostic accuracy. Cu...

Inside a Metastatic Fracture: Molecular Bases and New Potential Therapeutic Targets.

INTRODUCTION: Bone metastases and pathological fractures significantly impact the prognosis and quality of life in cancer patients. However, clinical ...