AIMC Topic: Arthroplasty, Replacement, Shoulder

Clear Filters Showing 11 to 20 of 20 articles

Novel robotic technology for the rapid intraoperative manufacture of patient-specific instrumentation allowing for improved glenoid component accuracy in shoulder arthroplasty: a cadaveric study.

Journal of shoulder and elbow surgery Oct 5, 2021
BACKGROUND: Accurate prosthesis placement in arthroplasty is an important factor in the long-term success of these interventions. Many types of guidance technology have been described to date often suffering from high costs, complex theater integrati...
Cadaver Shoulder Joint Arthroplasty Arthroplasty, Replacement, Shoulder Imaging, Three-Dimensional Robotics Surgery, Computer-Assisted Humans
View on PubMed DOI

The value of artificial neural networks for predicting length of stay, discharge disposition, and inpatient costs after anatomic and reverse shoulder arthroplasty.

Journal of shoulder and elbow surgery Jun 9, 2020
HYPOTHESIS/PURPOSE: The objective is to develop and validate an artificial intelligence model, specifically an artificial neural network (ANN), to predict length of stay (LOS), discharge disposition, and inpatient charges for primary anatomic total (...
Hospital Costs Hospital Charges Arthroplasty, Replacement, Shoulder Hemiarthroplasty Shoulder Injuries ROC Curve Models, Statistical Patient Discharge Osteoarthritis Middle Aged Machine Learning Postoperative Complications Forecasting Length of Stay Databases, Factual Female Reproducibility of Results Aged Aged, 80 and over Male Humans Neural Networks, Computer
View on PubMed DOI

Automated detection and classification of shoulder arthroplasty models using deep learning.

Skeletal radiology May 15, 2020
OBJECTIVE: To develop and evaluate the performance of deep convolutional neural networks (DCNN) to detect and identify specific total shoulder arthroplasty (TSA) models.
Humans Radiography Neural Networks, Computer Arthroplasty, Replacement, Shoulder Deep Learning ROC Curve
View on PubMed DOI

Construct validation of machine learning in the prediction of short-term postoperative complications following total shoulder arthroplasty.

Journal of shoulder and elbow surgery Aug 3, 2019
BACKGROUND: We aimed to demonstrate that supervised machine learning (ML) models can better predict postoperative complications after total shoulder arthroplasty (TSA) than comorbidity indices.
Hematocrit Patient Readmission Smoking Reoperation Operative Time Predictive Value of Tests Postoperative Complications Supervised Machine Learning Comorbidity Female Length of Stay Serum Albumin Aged ROC Curve Arthroplasty, Replacement, Shoulder Male Body Mass Index Middle Aged Age Factors Humans Blood Transfusion Forecasting Databases, Factual
View on PubMed DOI

Predicting Unplanned Return to Operating Room Following Primary Total Shoulder Arthroplasty: Insights from Fair and Explainable Ensemble Machine Learning.

Studies in health technology and informatics Sep 24, 2024
Reoperation is the most significant complication following any surgical procedure. Developing machine learning methods that predict the need for reoperation will allow for improved shared surgical decision making and patient-specific and preoperative...
Postoperative Complications Reoperation Operating Rooms Arthroplasty, Replacement, Shoulder Humans Machine Learning Female Male
View on PubMed DOI

What Is the Accuracy of Three Different Machine Learning Techniques to Predict Clinical Outcomes After Shoulder Arthroplasty?

Clinical orthopaedics and related research Oct 1, 2020
BACKGROUND: Machine learning techniques can identify complex relationships in large healthcare datasets and build prediction models that better inform physicians in ways that can assist in patient treatment decision-making. In the domain of shoulder ...
Treatment Outcome Predictive Value of Tests Female Pain Measurement Range of Motion, Articular Humans Aged Minimal Clinically Important Difference Machine Learning Arthroplasty, Replacement, Shoulder Male Middle Aged
View on PubMed DOI

A Novel Machine Learning Model Developed to Assist in Patient Selection for Outpatient Total Shoulder Arthroplasty.

The Journal of the American Academy of Orthopaedic Surgeons Jul 1, 2020
INTRODUCTION: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to develop a machine learning tool that may aid in patient selection for outpatient total should arthroplast...
Aged Pulmonary Disease, Chronic Obstructive Male Comorbidity Forecasting Decision Support Techniques Female Age Factors Patient Selection Sex Factors Outpatients Length of Stay ROC Curve Logistic Models Treatment Outcome Humans Machine Learning Arthroplasty, Replacement, Shoulder
View on PubMed DOI

Let's "recall" sensitivity and specificity: Letter to the Editor regarding Gowd et al: "Construct validation of machine learning in the prediction of short-term postoperative complications following total shoulder arthroplasty".

Journal of shoulder and elbow surgery Mar 1, 2020
Arthroplasty, Replacement, Shoulder Machine Learning Male Postoperative Complications Mental Recall Humans
View on PubMed DOI

Response to Chelli and Boileau: "Let's 'recall' sensitivity and specificity".

Journal of shoulder and elbow surgery Mar 1, 2020
Humans Machine Learning Postoperative Complications Mental Recall Arthroplasty, Replacement, Shoulder
View on PubMed DOI

A Robotic Glenohumeral Simulator for Investigating Prosthetic Implant Subluxation.

Journal of biomechanical engineering Jan 1, 2020
Total shoulder arthroplasty (TSA) is an effective treatment for glenohumeral (GH) osteoarthritis. However, it still suffers from a substantial rate of mechanical failure, which may be related to cyclic off-center loading of the humeral head on the gl...
Biomechanical Phenomena Robotics Shoulder Joint Mechanical Phenomena Arthroplasty, Replacement, Shoulder Shoulder Prosthesis Humans
View on PubMed DOI
Popular Topics
Recent Journals