Orthopedics

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

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Showing 2668-2688 of 5,212 articles
Joint segmentation and classification of hepatic lesions in ultrasound images using deep learning.

OBJECTIVES: To develop a convolutional neural network system to jointly segment and classify a hepat...

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and o...

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment.

Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patte...

A method for the automatic detection of myopia in Optos fundus images based on deep learning.

Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic ...

Deep learning to segment pelvic bones: large-scale CT datasets and baseline models.

PURPOSE: Pelvic bone segmentation in CT has always been an essential step in clinical diagnosis and ...

Automatic tip detection of surgical instruments in biportal endoscopic spine surgery.

BACKGROUND: Recent advances in robotics and deep learning can be used in endoscopic surgeries and ca...

Model construction and application for automated measurement of CE angle on pelvis orthograph based on MASK-R-CNN algorithm.

Developmental dysplasia of the hip (DDH) is a common orthopedic disease. A simple and cost-effective...

Adaptive SNN for Anthropomorphic Finger Control.

Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artifi...

Accelerated multicontrast reconstruction for synthetic MRI using joint parallel imaging and variable splitting networks.

PURPOSE: Synthetic magnetic resonance imaging (MRI) requires the acquisition of multicontrast images...

Deep learning approach to predict pain progression in knee osteoarthritis.

OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting pain pro...

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

Electron microscopy (EM) enables high-resolution visualization of protein distributions in biologica...

Optimal Bayesian Transfer Learning for Count Data.

There is often a limited amount of omics data to design predictive models in biomedicine. Knowing th...

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 femor...

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 mach...

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...

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 g...

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 affe...

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though ...

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; complicati...

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