Orthopedics

Deep learning approach to predict pain progression in knee osteoarthritis.

OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting pain progression in subjects with or at risk of knee osteoarthritis (OA).

A deep learning approach to identifying immunogold particles in electron microscopy images.

Electron microscopy (EM) enables high-resolution visualization of protein distributions in biological tissues. For detection, gold nanoparticles are typically used as an electron-dense marker for immunohistochemically labeled proteins. Manual annotation of gold particle labels is laborious and time consuming, as gold particle counts can exceed 100,000 across hundreds of image segments to obtain co...

Optimal Bayesian Transfer Learning for Count Data.

There is often a limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes...

Fall Detection With UWB Radars and CNN-LSTM Architecture.

Fall detection is a major challenge for researchers. Indeed, a fall can cause injuries such as femoral neck fracture, brain hemorrhage, or skin burns,...

Deep transfer learning can be used for the detection of hip joints in pelvis radiographs and the classification of their hip dysplasia status.

Reports of machine learning implementations in veterinary imaging are infrequent but changes in machine learning architecture and access to increased ...

Three-dimensional image volumes from two-dimensional digitally reconstructed radiographs: A deep learning approach in lower limb CT scans.

PURPOSE: Three-dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years n...

Application of machine learning techniques to physical and rehabilitative medicine.

Nowadays, digital information has increased exponentially in every field to such an extent that it generates huge amounts of electronic data, namely B...

Development and feasibility of a soft pneumatic-robotic glove to assist impaired hand function in quadriplegia patients: A pilot study.

One of the common disorders in people with quadriplegia is having a weak grip strength that can affect activities of daily living (ADL). This study pr...

Artificial intelligence for the classification of fractures around the knee in adults according to the 2018 AO/OTA classification system.

BACKGROUND: Fractures around the knee joint are inherently complex in terms of treatment; complication rates are high, and they are difficult to diagn...

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, survival often depends on their ability to perfo...

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 strategy. Purpose To evaluate the diagnostic performance...

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 and prognosis in fields ranging from dermatology t...

Deep joint learning for language recognition.

Deep learning methods for language recognition have achieved promising performance. However, most of the studies focus on frameworks for single types ...

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 have focused exclusively on single-label waste clas...

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 transmission method. The characterization of long c...

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 structures that are relevant for diagnosis and treatme...

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

Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in d...

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 assessment of knee osteoarthritis severity in radiographs...

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 joint (TMJ) disc perforation based on the findings ...

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 pain. Only limited diagnostic tools such as magnetic ...