Orthopedics

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

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Showing 2164-2184 of 5,212 articles
Diagnostic advantage of thin slice 2D MRI and multiplanar reconstruction of the knee joint using deep learning based denoising approach.

The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton...

Automatic Grading Assessments for Knee MRI Cartilage Defects via Self-ensembling Semi-supervised Learning with Dual-Consistency.

Knee cartilage defects caused by osteoarthritis are major musculoskeletal disorders, leading to join...

Deep-learning synthesized pseudo-CT for MR high-resolution pediatric cranial bone imaging (MR-HiPCB).

PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma...

Pragmatic Prediction of Excessive Length of Stay After Cervical Spine Surgery With Machine Learning and Validation on a National Scale.

BACKGROUND: Extended postoperative hospital stays are associated with numerous clinical risks and in...

MTPA_Unet: Multi-Scale Transformer-Position Attention Retinal Vessel Segmentation Network Joint Transformer and CNN.

Retinal vessel segmentation is extremely important for risk prediction and treatment of many major d...

Comparison of Transfer Learning Models in Pelvic Tilt and Rotation Measurement in Pediatric Anteroposterior Pelvic Radiographs.

The rotation and tilt of the pelvis during anteroposterior pelvic radiography can lead to misdiagnos...

Adapting a low-count acquisition of the bone scintigraphy using deep denoising super-resolution convolutional neural network.

PURPOSE: Deep-layer learning processing may improve contrast imaging with greater precision in low-c...

Multi-class retinal fluid joint segmentation based on cascaded convolutional neural networks.

. Retinal fluid mainly includes intra-retinal fluid (IRF), sub-retinal fluid (SRF) and pigment epith...

Improved Productivity Using Deep Learning-assisted Reporting for Lumbar Spine MRI.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involve...

Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest.

Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM)...

Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model.

BACKGROUND We aimed to develop and evaluate a deep learning-based method for fully automatic segment...

Ensemble deep learning model for predicting anterior cruciate ligament tear from lateral knee radiograph.

OBJECTIVE: To develop an ensemble deep learning model (DLM) predicting anterior cruciate ligament (A...

Automatic Cobb angle measurement method based on vertebra segmentation by deep learning.

The accuracy of the Cobb measurement is essential for the diagnosis and treatment of scoliosis. Manu...

Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis.

OBJECTIVES: Recent studies have shown that deep learning based on pre-treatment positron emission to...

Prediction of abrasive wears behavior of dental composites using an artificial neural network.

Resin composites are widely used as dental restorative materials since dental parts are subjected to...

Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning.

Cardiovascular diseases (CVD) are the leading cause of death worldwide. People affected by CVDs may ...

Recurrent neural networks as kinematics estimator and controller for redundant manipulators subject to physical constraints.

Redundant manipulators could be efficient tools in industrial production as a result of their dexter...

Force and Torque Characterization in the Actuation of a Walking-Assistance, Cable-Driven Exosuit.

Soft exosuits stand out when it comes to the development of walking-assistance devices thanks to bot...

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