Orthopedics

A Randomized Controlled Trial of an Intelligent Robotic Response to Joint Attention Intervention System.

Although there has been growing interest in utilizing robots for intervention in autism spectrum disorder (ASD), there have been very few controlled trials to assess the actual impacts of such systems on social communication vulnerabilities. This study reports a randomized controlled trial to investigate a robot-mediated response to joint attention intervention in a small (23 recruited; 20 complet...

Deep Convolutional Neural Network-Based Diagnosis of Anterior Cruciate Ligament Tears: Performance Comparison of Homogenous Versus Heterogeneous Knee MRI Cohorts With Different Pulse Sequence Protocols and 1.5-T and 3-T Magnetic Field Strengths.

OBJECTIVES: The aim of this study was to clinically validate a Deep Convolutional Neural Network (DCNN) for the detection of surgically proven anterior cruciate ligament (ACL) tears in a large patient cohort and to analyze the effect of magnetic resonance examinations from different institutions, varying protocols, and field strengths.

Automatic Segmentation of Meniscus in Multispectral MRI Using Regions with Convolutional Neural Network (R-CNN).

The meniscus has a significant function in human anatomy, and Magnetic Resonance Imaging (MRI) has an essential role in meniscus examination. Due to a...

Re: Phene et al.: Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs (Ophthalmology. 2019;126:1627-1639).

Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care.

Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on "one-size-...

A Novel Machine Learning Model Developed to Assist in Patient Selection for Outpatient Total Shoulder Arthroplasty.

INTRODUCTION: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to devel...

Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?

BACKGROUND: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used ...

Data for registry and quality review can be retrospectively collected using natural language processing from unstructured charts of arthroplasty patients.

AIMS: Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry partic...

[Rehabilitation of traumatic spinal cord injury with lower limb exoskeleton].

In recent years, several technological innovations have emerged to improve the rehabilitation of traumatic spinal cord injury (SCI). Among them, robot...

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer.

FDG PET/CT imaging is commonly used in diagnosis and follow-up of metastatic breast cancer, but its quantitative analysis is complicated by the number...

MRI-SegFlow: a novel unsupervised deep learning pipeline enabling accurate vertebral segmentation of MRI images.

Most deep learning based vertebral segmentation methods require laborious manual labelling tasks. We aim to establish an unsupervised deep learning pi...

Learning Conflicts for C-arm Kinematic Modeling using Artificial Intelligence.

During common surgical tasks related to orthopedic applications, it is necessary to carefully manipulate a mobile C-arm device to achieve the desired ...

Design and Preliminary Implementation of an Air Microfluidics Enabled Soft Robotic Knee Brace Towards the Management of Osteoarthritis.

A dynamic and low-profile unloader tibiofemoral knee brace is designed and prototyped by synergizing concepts from the fields of microfluidics and sof...

Autonomous Control of a Tendon-driven Robotic Limb with Elastic Elements Reveals that Added Elasticity can Enhance Learning.

Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also ad...

Automatic Tracking of the Muscle Tendon Junction in Healthy and Impaired Subjects using Deep Learning.

Recording muscle tendon junction displacements during movement, allows separate investigation of the muscle and tendon behaviour, respectively. In ord...

Robotic Assessments of Proprioception and the Impact of Age.

We examined different methods of robotic proprioception assessment and provided comparison with the wrist position sense test gold standard assessment...

[Design and performance analysis of elastic temporomandibular joint structure of biomimetic masticatory robot].

Masticatory robots have a broad application prospect in the field of denture material tests and mandible rehabilitation. Mechanism type of temporomand...

Image-guidance, Robotics, and the Future of Spine Surgery.

Spine surgery has seen considerable advancements over the last 2 decades, particularly in the fields of image-guidance and robotics. These technologie...

Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.

BACKGROUND: Deep learning (DL) has demonstrated human expert levels of performance for medical image classification in a wide array of medical fields,...

An Approach to Robotic Testing of the Wrist Using Three-Dimensional Imaging and a Hybrid Testing Methodology.

Robotic technology is increasingly used for sophisticated in vitro testing designed to understand the subtleties of joint biomechanics. Typically, the...