Orthopedics

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlated. Most of existing joint learning approaches require hand-crafted feature representations for MR images. Since hand-crafted features of MRI and class...

Effectiveness of bisphosphonate combined with activated vitamin D in patients with aromatase inhibitor-induced osteoporosis after breast cancer operation.

OBJECTIVES: We compared the effectiveness of bisphosphonates combined with activated vitamin D administered for therapy of aromatase inhibitor-induced osteoporosis after a breast cancer operation and primary postmenopausal osteoporosis through propensity score matching.

A Novel Morphological Analysis of DXA-DICOM Images by Artificial Neural Networks for Estimating Bone Mineral Density in Health and Disease.

One of the best methods for diagnosing bone disease in humans is site-specific and total bone mineral density (BMD) measurements by Dual-energy X-ray ...

Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care mod...

The impact of robotic intervention on joint attention in children with autism spectrum disorders.

BACKGROUND: A growing body of anecdotal evidence indicates that the use of robots may provide unique opportunities for assisting children with autism ...

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deteriorat...

Performance of the deep convolutional neural network based magnetic resonance image scoring algorithm for differentiating between tuberculous and pyogenic spondylitis.

The purpose of this study was to evaluate the performance of the deep convolutional neural network (DCNN) in differentiating between tuberculous and p...

Can Deep Learning Improve Genomic Prediction of Complex Human Traits?

The genetic analysis of complex traits does not escape the current excitement around artificial intelligence, including a renewed interest in "deep le...

Evaluation of analgesic efficacy of dexmedetomidine as adjuvant with ropivacaine in ultrasound-guided adductor canal block in patients following anterior cruciate ligament reconstruction surgeries.

INTRODUCTION: Local anaesthetic (LA) with highly selective alpha-2 agonist dexmedetomidine has not been evaluated in adductor canal block (ACB) for ar...

Dixon-VIBE Deep Learning (DIVIDE) Pseudo-CT Synthesis for Pelvis PET/MR Attenuation Correction.

Whole-body attenuation correction (AC) is still challenging in combined PET/MR scanners. We describe Dixon-VIBE Deep Learning (DIVIDE), a deep-learnin...

Wearable Sensor Data to Track Subject-Specific Movement Patterns Related to Clinical Outcomes Using a Machine Learning Approach.

Wearable sensors can provide detailed information on human movement but the clinical impact of this information remains limited. We propose a machine ...

Evaluation of the Bactericidal and Fungicidal Activities of Poly([2-(methacryloyloxy)ethyl]trimethyl Ammonium Chloride)(Poly (METAC))-Based Materials.

Poly([2-(methacryloyloxy)ethyl]trimethyl ammonium chloride) (METAC) and the gels were prepared and evaluated for their bactericidal and fungicidal act...

Drug-drug interaction extraction from biomedical texts using long short-term memory network.

The simultaneous administration of multiple drugs increases the probability of interaction among them, as one drug may affect the activities of others...

Effect of Initial Graft Tension During Calcaneofibular Ligament Reconstruction on Ankle Kinematics and Laxity.

BACKGROUND: Although a variety of surgical procedures for lateral ankle ligament reconstruction have frequently been reported, little is known about t...

Automated dendritic spine detection using convolutional neural networks on maximum intensity projected microscopic volumes.

BACKGROUND: Dendritic spines are structural correlates of excitatory synapses in the brain. Their density and structure are shaped by experience, poin...

Automatic hyoid bone detection in fluoroscopic images using deep learning.

The displacement of the hyoid bone is one of the key components evaluated in the swallow study, as its motion during swallowing is related to overall ...

Mechanical Design and Control Strategy for Hip Joint Power Assisting.

The basic requirements for mechanical design and control strategy are adapting to human joint movements and building an interaction model between huma...

Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.

Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathways are largely unclear. The aim of this study was...

Deep convolutional neural network-based segmentation and classification of difficult to define metastatic spinal lesions in 3D CT data.

This paper aims to address the segmentation and classification of lytic and sclerotic metastatic lesions that are difficult to define by using spinal ...

Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.

OBJECTIVE: Radiographic bone age assessment (BAA) is used in the evaluation of pediatric endocrine and metabolic disorders. We previously developed an...