Orthopedics

Spatiotemporal Co-Attention Recurrent Neural Networks for Human-Skeleton Motion Prediction.

Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling sequential data, recent works utilize RNNs to model human-skeleton motions on the observed motion sequence and predict future human motions. However, these methods disregard the existence of the spatial coherence among joints and the tem...

Noise exposure during robot-assisted total knee arthroplasty.

The aim of the study was to examine the noise exposure for operating theater staff during total knee arthroplasty (TKA) with three different robot systems. There is already evidence that noise exposure during TKA performed manually exceeds recommended guidelines for occupational noise. Therefore, if surgical staff is exposed to it for several years, the development of noise-inducing hearing loss (...

Development of a Robotic Spine Surgery Program: Rationale, Strategy, Challenges, and Monitoring of Outcomes After Implementation.

Surgical robots were invented in the 1980s, and since then, robotic-assisted surgery has become commonplace. In the field of spine surgery, robotic as...

Rise of the Machines? Artificial Intelligence May Represent the Future but It Is Not Ready for Prime Time: Commentary on an article by Evan M. Polce, BS, et al.: "Efficacy and Applications of Artificial Intelligence and Machine Learning Analyses in Total Joint Arthroplasty. A Call for Improved Reporting".

Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms.

: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vita...

Use of artificial intelligence in activating the role of Saudi universities in joint scientific research between university teachers and students.

Scientific research in Saudi Arabia's universities has undergone significant changes in recent years with the speed of higher education expansion and ...

FractureNet: A 3D Convolutional Neural Network Based on the Architecture of m-Ary Tree for Fracture Type Identification.

To address the problem of automatic identification of fine-grained fracture types, in this paper, we propose a novel framework using 3D convolutional ...

A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.

The ideal observer (IO) sets an upper performance limit among all observers and has been advocated for assessing and optimizing imaging systems. For g...

Deep Learning Based Joint PET Image Reconstruction and Motion Estimation.

Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion...

Adaptive Contrast for Image Regression in Computer-Aided Disease Assessment.

Image regression tasks for medical applications, such as bone mineral density (BMD) estimation and left-ventricular ejection fraction (LVEF) predictio...

Using deep transfer learning to detect scoliosis and spondylolisthesis from x-ray images.

Recent years have witnessed wider prevalence of vertebral column pathologies due to lifestyle changes, sedentary behaviors, or injuries. Spondylolisth...

Diagnostic performance for detecting bone marrow edema of the hip on dual-energy CT: Deep learning model vs. musculoskeletal physicians and radiologists.

PURPOSE: To compare the diagnostic performance of a deep learning (DL) model with that of musculoskeletal physicians and radiologists for detecting bo...

Deep Neural Network Recognition of Rivet Joint Defects in Aircraft Products.

The mathematical statement of the problem of recognizing rivet joint defects in aircraft products is given. A computational method for the recognition...

Underwater acoustic target recognition method based on a joint neural network.

To improve the recognition accuracy of underwater acoustic targets by artificial neural network, this study presents a new recognition method that int...

Deep Learning-Based Multimodal 3 T MRI for the Diagnosis of Knee Osteoarthritis.

The objective of this study was to investigate the application effect of deep learning model combined with different magnetic resonance imaging (MRI) ...

Deep Learning for Automatic Hyoid Tracking in Videofluoroscopic Swallow Studies.

The hyoid bone excursion is one of the most important gauges of larynx elevation in swallowing, contributing to airway protection and bolus passage in...

Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures.

In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fract...

Improved diagnostic performance of plain radiography for cervical ossification of the posterior longitudinal ligament using deep learning.

BACKGROUND: A high false-negative rate has been reported for the diagnosis of ossification of the posterior longitudinal ligament (OPLL) using plain r...

Does proximal versus distal injury location of the medial ulnar collateral ligament of the elbow differentially impact elbow stability? An ultrasound-guided and robot-assisted biomechanical study.

BACKGROUND: The location (proximal vs. distal) of elbow medial ulnar collateral ligament (MUCL) tears impacts clinical outcomes of nonoperative treatm...

Toward an artificial intelligence-assisted framework for reconstructing the digital twin of vertebra and predicting its fracture response.

This article presents an effort toward building an artificial intelligence (AI) assisted framework, coined ReconGAN, for creating a realistic digital ...