Orthopedics

Cervical Spondylosis Diagnosis Based on Convolutional Neural Network with X-ray Images.

The increase in Cervical Spondylosis cases and the expansion of the affected demographic to younger patients have escalated the demand for X-ray screening. Challenges include variability in imaging technology, differences in equipment specifications, and the diverse experience levels of clinicians, which collectively hinder diagnostic accuracy. In response, a deep learning approach utilizing a Res...

Prediction of 30-Day Mortality Following Revision Total Hip and Knee Arthroplasty: Machine Learning Algorithms Outperform CARDE-B, 5-Item, and 6-Item Modified Frailty Index Risk Scores.

BACKGROUND: Although risk calculators are used to prognosticate postoperative outcomes following revision total hip and knee arthroplasty (total joint arthroplasty [TJA]), machine learning (ML) based predictive tools have emerged as a promising alternative for improved risk stratification. This study aimed to compare the predictive ability of ML models for 30-day mortality following revision TJA t...

Enhancing wrist arthroscopy: artificial intelligence applications for bone structure recognition using machine learning.

INTRODUCTION: Wrist arthroscopy is a rapidly expanding surgical discipline, but has a long and challenging learning curve. One of its difficulties is ...

Real-time sports injury monitoring system based on the deep learning algorithm.

In response to the low real-time performance and accuracy of traditional sports injury monitoring, this article conducts research on a real-time injur...

Machine-learning models for diagnosis of rotator cuff tears in osteoporosis patients based on anteroposterior X-rays of the shoulder joint.

OBJECTIVE: This study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in patients with Osteoporosis (OP) through the analys...

Characterization of clinical data for patient stratification in moderate osteoarthritis with support vector machines, regulatory network models, and verification against osteoarthritis Initiative data.

Knee osteoarthritis (OA) diagnosis is based on symptoms, assessed through questionnaires such as the WOMAC. However, the inconsistency of pain recordi...

An interpretable data-driven prediction model to anticipate scoliosis in spinal muscular atrophy in the era of (gene-) therapies.

5q-spinal muscular atrophy (SMA) is a neuromuscular disorder (NMD) that has become one of the first 5% treatable rare diseases. The efficacy of new SM...

Bridging Imaging and Clinical Scores in Parkinson's Progression via Multimodal Self-Supervised Deep Learning.

Neurodegenerative diseases pose a formidable challenge to medical research, demanding a nuanced understanding of their progressive nature. In this reg...

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.

BACKGROUND: Osteoporosis (OP), the "silent epidemic" of our century, poses a significant challenge to public health, predominantly affecting postmenop...

SAMCF: Adaptive global style alignment and multi-color spaces fusion for joint optic cup and disc segmentation.

The optic cup (OC) and optic disc (OD) are two critical structures in retinal fundus images, and their relative positions and sizes are essential for ...

A quality and readability comparison of artificial intelligence and popular health website education materials for common hand surgery procedures.

INTRODUCTION: ChatGPT and its application in producing patient education materials for orthopedic hand disorders has not been extensively studied. Thi...

Characterization and quantification of in-vitro equine bone resorption in 3D using μCT and deep learning-aided feature segmentation.

High cyclic strains induce formation of microcracks in bone, triggering targeted bone remodeling, which entails osteoclastic resorption. Racehorse bon...

Deep Learning Method for Rapid Simultaneous Multistructure Temporal Bone Segmentation.

OBJECTIVE: To develop and validate a deep learning algorithm for the automated segmentation of key temporal bone structures from clinical computed tom...

Unlocking the full potential of mesenchymal stromal cell therapy for osteoarthritis through machine learning-based in silico trials.

Despite the potential of mesenchymal stromal cells (MSCs) in osteoarthritis (OA) treatment, the challenge lies in addressing their therapeutic inconsi...

Deep learning for temporomandibular joint arthropathies: A systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: The accurate diagnosis of temporomandibular disorders continues to be a challenge, despite the existence of internationally ...

JOINEDTrans: Prior guided multi-task transformer for joint optic disc/cup segmentation and fovea detection.

Deep learning-based image segmentation and detection models have largely improved the efficiency of analyzing retinal landmarks such as optic disc (OD...

Automatic segmentation of femoral tumors by nnU-net.

BACKGROUND: Metastatic femoral tumors may lead to pathological fractures during daily activities. A CT-based finite element analysis of a patient's fe...

Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks.

Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. Th...

Shape completion in the dark: completing vertebrae morphology from 3D ultrasound.

PURPOSE: Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs a...

MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study.

Magnetic Resonance Imaging (MRI) is increasingly being used in treatment planning due to its superior soft tissue contrast, which is useful for tumor ...