Orthopedics

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

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Using a biologically mimicking climbing robot to explore the performance landscape of climbing in lizards.

Locomotion is a key aspect associated with ecologically relevant tasks for many organisms, therefore...

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT.

Background It is important to diagnose sclerotic bone lesions in order to determine treatment strate...

Introduction to The Spine Journal special issue on artificial intelligence and machine learning.

In the last 5 years, artificial intelligence (AI) algorithms have made rapid advances for diagnosis ...

Deep joint learning for language recognition.

Deep learning methods for language recognition have achieved promising performance. However, most of...

A deep convolutional neural network to simultaneously localize and recognize waste types in images.

Accurate waste classification is key to successful waste management. However, most current studies h...

A deep cascaded segmentation of obstructive sleep apnea-relevant organs from sagittal spine MRI.

PURPOSE: The main purpose of this work was to develop an efficient approach for segmentation of stru...

Deep Learning Analysis of Ultrasonic Guided Waves for Cortical Bone Characterization.

Ultrasonic guided waves (UGWs) propagating in the long cortical bone can be measured via the axial t...

Machine learning prediction of pathologic myopia using tomographic elevation of the posterior sclera.

Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced p...

Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists.

UNLABELLED: A fully-automated deep learning algorithm matched performance of radiologists in assessm...

Using deep learning to predict temporomandibular joint disc perforation based on magnetic resonance imaging.

The goal of this study was to develop a deep learning-based algorithm to predict temporomandibular j...

Imbalanced Loss-Integrated Deep-Learning-Based Ultrasound Image Analysis for Diagnosis of Rotator-Cuff Tear.

A rotator cuff tear (RCT) is an injury in adults that causes difficulty in moving, weakness, and pai...

Development and validation of a sensitive LC-MS/MS method for pioglitazone: application towards pharmacokinetic and tissue distribution study in rats.

In the present study, a sensitive LC-MS/MS method was developed and validated to measure pioglitazon...

Multitask Feature Learning Meets Robust Tensor Decomposition for EEG Classification.

In this article, we study a tensor-based multitask learning (MTL) method for classification. Taking ...

Opposite valence social information provided by bio-robotic demonstrators shapes selection processes in the green bottle fly.

Social learning represents a high-level complex process to acquire information about the environment...

Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients.

Manual segmentation of muscle and adipose compartments from computed tomography (CT) axial images is...

Critical evaluation of deep neural networks for wrist fracture detection.

Wrist Fracture is the most common type of fracture with a high incidence rate. Conventional radiogra...

Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis.

BACKGROUND: Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It i...

Using artificial intelligence to diagnose fresh osteoporotic vertebral fractures on magnetic resonance images.

BACKGROUND CONTEXT: Accurate diagnosis of osteoporotic vertebral fracture (OVF) is important for imp...

Machine learning for the prediction of bone metastasis in patients with newly diagnosed thyroid cancer.

OBJECTIVES: This study aimed to establish a machine learning prediction model that can be used to pr...

Do Radiographic Assessments of Periodontal Bone Loss Improve with Deep Learning Methods for Enhanced Image Resolution?

Resolution plays an essential role in oral imaging for periodontal disease assessment. Nevertheless,...

Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors.

OBJECTIVES: To build and validate random forest (RF) models for the classification of bone tumors ba...

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