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Arthroscopy

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Deep Learning-Based Image Feature with Arthroscopy-Aided Early Diagnosis and Treatment of Meniscus Injury of Knee Joint.

Journal of healthcare engineering
The aim of this study is to explore the clinical effect of deep learning-based MRI-assisted arthroscopy in the early treatment of knee meniscus sports injury. Based on convolutional neural network algorithm, Adam algorithm was introduced to optimize ...

Deep Learning-Based Magnetic Resonance Imaging Image Features for Diagnosis of Anterior Cruciate Ligament Injury.

Journal of healthcare engineering
To study and explore the adoption value of magnetic resonance imaging (MRI) in the diagnosis of anterior cruciate ligament (ACL) injuries, a multimodal feature fusion model based on deep learning was proposed for MRI diagnosis. After the related perf...

Duration of Care and Operative Time Are the Primary Drivers of Total Charges After Ambulatory Hip Arthroscopy: A Machine Learning Analysis.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
PURPOSE: To develop a machine learning algorithm to predict total charges after ambulatory hip arthroscopy and create a risk-adjusted payment model based on patient comorbidities.

[Management of the nondisplaced type Herbert D1 scaphoid fracture with robot navigation combined with wrist arthroscopy].

Zhonghua yi xue za zhi
To investigate the feasibility and the clinical efficiency of robot navigation combined with wrist arthroscopy in minimally invasive treatment of nondisplaced type Herbert D1 scaphoid fracture. A retrospective analysis was performed on 9 patients who...

Developing a machine learning algorithm to predict probability of retear and functional outcomes in patients undergoing rotator cuff repair surgery: protocol for a retrospective, multicentre study.

BMJ open
INTRODUCTION: The effectiveness of rotator cuff tear repair surgery is influenced by multiple patient-related, pathology-centred and technical factors, which is thought to contribute to the reported retear rates between 17% and 94%. Adequate patient ...

Prediction of Retear After Arthroscopic Rotator Cuff Repair Based on Intraoperative Arthroscopic Images Using Deep Learning.

The American journal of sports medicine
BACKGROUND: It is challenging to predict retear after arthroscopic rotator cuff repair (ARCR). The usefulness of arthroscopic intraoperative images as predictors of the ARCR prognosis has not been analyzed.

Evaluation of a newly designed deep learning-based algorithm for automated assessment of scapholunate distance in wrist radiography as a surrogate parameter for scapholunate ligament rupture and the correlation with arthroscopy.

La Radiologia medica
PURPOSE: Not diagnosed or mistreated scapholunate ligament (SL) tears represent a frequent cause of degenerative wrist arthritis. A newly developed deep learning (DL)-based automated assessment of the SL distance on radiographs may support clinicians...

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

International orthopaedics
PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning w...

MRI-based automated multitask deep learning system to evaluate supraspinatus tendon injuries.

European radiology
OBJECTIVE: To establish an automated, multitask, MRI-based deep learning system for the detailed evaluation of supraspinatus tendon (SST) injuries.