Orthopedics

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

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Showing 3193-3213 of 5,223 articles
Robust auto-weighted projective low-rank and sparse recovery for visual representation.

Most existing low-rank and sparse representation models cannot preserve the local manifold structure...

Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments.

Traditionally, chemists have relied on years of training and accumulated experience in order to disc...

Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction.

PURPOSE: To introduce a combined machine learning (ML)- and physics-based image reconstruction frame...

Combining convolutional neural networks and star convex cuts for fast whole spine vertebra segmentation in MRI.

BACKGROUND AND OBJECTIVE: We propose an automatic approach for fast vertebral body segmentation in t...

Effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity in women.

PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and...

Deep Belief CNN Feature Representation Based Content Based Image Retrieval for Medical Images.

Avascular Necrosis (AN) is a cause of muscular-skeletal disability. As it is common amongst the youn...

Adaptive Augmentation of Medical Data Using Independently Conditional Variational Auto-Encoders.

Current deep supervised learning methods typically require large amounts of labeled data for trainin...

Toward Automated 3D Spine Reconstruction from Biplanar Radiographs Using CNN for Statistical Spine Model Fitting.

To date, 3D spine reconstruction from biplanar radiographs involves intensive user supervision and s...

Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

OBJECTIVES: To evaluate the performance of a novel three-dimensional (3D) joint convolutional and re...

Incorporated region detection and classification using deep convolutional networks for bone age assessment.

Bone age assessment plays an important role in the endocrinology and genetic investigation of patien...

JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation.

OBJECTIVE: The purpose of this paper is to propose a novel algorithm for joint optic disc and cup se...

Regression Algorithm of Bone Age Estimation of Knee-joint Based on Principal Component Analysis and Support Vector Machine.

Objective To establish a regression algorithm model that applies to bone age estimation of Xinjiang ...

Automatic localization of anatomical regions in medical ultrasound images of rheumatoid arthritis using deep learning.

The pace of population aging is growing faster worldwide. The quality of life of the aging populatio...

Serum Pyridinoline is Associated With Radiographic Joint Erosions in Rheumatoid Arthritis.

OBJECTIVES: This study aims to compare the serum pyridinoline (Pyd) levels between rheumatoid arthri...

High-field mr diffusion-weighted image denoising using a joint denoising convolutional neural network.

BACKGROUND: Low signal-to-noise ratio (SNR) has been a major limiting factor for the application of ...

Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.

OBJECTIVE: Clinical care guidelines recommend that newly diagnosed prostate cancer patients at high ...

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

OBJECTIVE: Knee osteoarthritis (KOA) is a heterogeneous condition representing a variety of potentia...

Machine Learning for Diagnosis of Hematologic Diseases in Magnetic Resonance Imaging of Lumbar Spines.

We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate ...

Simulating Dual-Energy X-Ray Absorptiometry in CT Using Deep-Learning Segmentation Cascade.

PURPOSE: Osteoporosis is an underdiagnosed condition despite effective screening modalities. Dual-en...

A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data.

A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine o...

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