Orthopedics

Latest AI and machine learning research in orthopedics for healthcare professionals.

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Showing 1408-1428 of 5,200 articles
Automatic Segmentation and Radiologic Measurement of Distal Radius Fractures Using Deep Learning.

BACKGROUND: Recently, deep learning techniques have been used in medical imaging studies. We present...

A deep learning knowledge distillation framework using knee MRI and arthroscopy data for meniscus tear detection.

To construct a deep learning knowledge distillation framework exploring the utilization of MRI alon...

Using AI to Write a Review Article Examining the Role of the Nervous System on Skeletal Homeostasis and Fracture Healing.

PURPOSE OF REVIEW: Three review articles have been written that discuss the roles of the central and...

Artificial Intelligence-enabled Chest X-ray Classifies Osteoporosis and Identifies Mortality Risk.

A deep learning model was developed to identify osteoporosis from chest X-ray (CXR) features with hi...

Glenohumeral joint force prediction with deep learning.

Deep learning models (DLM) are efficient replacements for computationally intensive optimization tec...

Diagnostic accuracy of an artificial intelligence algorithm versus radiologists for fracture detection on cervical spine CT.

OBJECTIVES: To compare diagnostic accuracy of a deep learning artificial intelligence (AI) for cervi...

A Deep-Learning Model for Diagnosing Fresh Vertebral Fractures on Magnetic Resonance Images.

BACKGROUND: The accurate diagnosis of fresh vertebral fractures (VFs) was critical to optimizing tre...

Effect of Zoledronic Acid in Hepatic Osteodystrophy: A Double-Blinded Placebo-Controlled Trial.

PURPOSE: Literature on the treatment of pre-transplant hepatic osteodystrophy (HOD) is limited. The ...

Bioinformatic analysis of related immune cell infiltration and key genes in the progression of osteonecrosis of the femoral head.

OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a common orthopedic condition that will promp...

Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.

PURPOSE: Patient-to-image registration is a preliminary step required in surgical navigation based o...

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance ima...

Automated digital templating of component sizing is accurate in robotic total hip arthroplasty when compared to predicate software.

Accurate pre-operative templating of prosthesis components is an essential factor in successful tota...

Application of robot navigation system for insertion of femoral neck system in the treatment of femoral neck fracture.

PURPOSE: To evaluate the short-term clinical efficacy and advantages of surgery robot positioning sy...

Simulated outcomes for durotomy repair in minimally invasive spine surgery.

Minimally invasive spine surgery (MISS) is increasingly performed using endoscopic and microscopic v...

Approaching expert-level accuracy for differentiating ACL tear types on MRI with deep learning.

Treatment for anterior cruciate ligament (ACL) tears depends on the condition of the ligament. We ai...

Predicting saturated and near-saturated hydraulic conductivity using artificial neural networks and multiple linear regression in calcareous soils.

Hydraulic conductivity (Kψ) is one of the most important soil properties that influences water and c...

Joint representation of molecular networks from multiple species improves gene classification.

Network-based machine learning (ML) has the potential for predicting novel genes associated with nea...

Machine-learning-based coordination of powered ankle-foot orthosis and functional electrical stimulation for gait control.

This study proposes a novel gait rehabilitation method that uses a hybrid system comprising a powere...

Diagnostic evaluation of deep learning accelerated lumbar spine MRI.

BACKGROUND AND PURPOSE: Deep learning (DL) accelerated MR techniques have emerged as a promising app...

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