AIMC Topic: Arthroplasty, Replacement, Hip

Clear Filters Showing 91 to 100 of 143 articles

Fully automatic estimation of pelvic sagittal inclination from anterior-posterior radiography image using deep learning framework.

Computer methods and programs in biomedicine Dec 23, 2019
BACKGROUND AND OBJECTIVE: Malposition of the acetabular component causes dislocation and prosthetic impingement after Total Hip Arthroplasty (THA), which significantly affects the postoperative quality of life and implant longevity. The position of t...
Deep Learning Image Processing, Computer-Assisted Pelvis Automation Arthroplasty, Replacement, Hip Humans Neural Networks, Computer Tomography, X-Ray Computed
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Artificial neural network metamodel for sensitivity analysis in a total hip replacement health economic model.

Expert review of pharmacoeconomics & outcomes research Sep 13, 2019
: Metamodels have been used to approximate complex simulations and have many applications with sensitivity analysis, optimization, etc. However, their use in health economics is very limited. Application of artificial neural network (ANN) with a heal...
Neural Networks, Computer Computer Simulation Models, Economic Quality-Adjusted Life Years Linear Models Humans Arthroplasty, Replacement, Hip Normal Distribution
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Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling.

IEEE transactions on medical imaging Sep 10, 2019
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...
Arthroplasty, Replacement, Hip Hip Patient-Specific Modeling Neural Networks, Computer Tomography, X-Ray Computed Female Humans Male Deep Learning Image Processing, Computer-Assisted Muscle, Skeletal Thigh Bayes Theorem
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What Can We Expect Following Anterior Total Hip Arthroplasty on a Regular Operating Table? A Validation Study of an Artificial Intelligence Algorithm to Monitor Adverse Events in a High-Volume, Nonacademic Setting.

The Journal of arthroplasty Aug 3, 2019
BACKGROUND: Quality monitoring is increasingly important to support and assure sustainability of the orthopedic practice. Surgeons in nonacademic settings often lack resources to accurately monitor quality of care. Widespread use of electronic medica...
Electronic Health Records Humans Postoperative Complications Artificial Intelligence Arthroplasty, Replacement, Hip Algorithms Operating Tables
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Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial.

The Journal of arthroplasty Jul 24, 2019
BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PG...
Male Middle Aged Pilot Projects Wearable Electronic Devices Signal Processing, Computer-Assisted Algorithms Prospective Studies Female Aged Patient Reported Outcome Measures Monitoring, Ambulatory Postoperative Period Arthroplasty, Replacement, Hip Osteoarthritis, Knee Knee Joint Outcome Assessment, Health Care Range of Motion, Articular Arthroplasty, Replacement, Knee Humans Machine Learning Osteoarthritis, Hip
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Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty.

The Journal of arthroplasty Jun 13, 2019
BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study is to develop machine learning algorithms...
Aged Male Middle Aged Risk Assessment Logistic Models Pain, Postoperative Analgesics, Opioid Opioid-Related Disorders Postoperative Period Humans Machine Learning Algorithms Retrospective Studies Female Arthroplasty, Replacement, Hip Prescriptions
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Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review.

The Journal of arthroplasty Jun 11, 2019
BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. Lower extremity arthroplasty is uniquely positioned to mos...
Arthroplasty, Replacement, Hip Health Care Costs Machine Learning Treatment Outcome Lower Extremity Gait Arthroplasty, Replacement, Knee Humans Artificial Intelligence
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Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

The Journal of arthroplasty Jun 3, 2019
BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability to advance value-based healthcare by better predicting patient outcomes and costs of a given treatm...
Inpatients Outcome Assessment, Health Care Arthroplasty, Replacement, Knee New York Arthroplasty, Replacement, Hip Orthopedic Procedures Orthopedics Adolescent Child, Preschool Child ROC Curve Lower Extremity Male Middle Aged Infant Deep Learning Humans Neural Networks, Computer Databases, Factual Female Infant, Newborn Aged Young Adult Adult
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Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model.

The Journal of arthroplasty May 2, 2019
BACKGROUND: The primary objective was to develop and test an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition for total hip arthroplasty. The secondary objective was to create...
Social Class Health Care Costs Osteoarthritis, Hip Fees and Charges Female Reproducibility of Results Aged Aged, 80 and over ROC Curve Humans Male United States Databases, Factual Comorbidity Inpatients Deep Learning Arthroplasty, Replacement, Hip Length of Stay Preoperative Period Cohort Studies
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Bone texture analysis for prediction of incident radiographic hip osteoarthritis using machine learning: data from the Cohort Hip and Cohort Knee (CHECK) study.

Osteoarthritis and cartilage Feb 28, 2019
OBJECTIVE: To assess the ability of radiography-based bone texture variables in proximal femur and acetabulum to predict incident radiographic hip osteoarthritis (rHOA) over a 10 years period.
Fractals Osteophyte Image Processing, Computer-Assisted Body Mass Index Acetabulum Area Under Curve Radiography Netherlands Male Arthroplasty, Replacement, Hip Humans Middle Aged Femur Machine Learning Incidence Osteoarthritis, Hip Prospective Studies Cohort Studies Female ROC Curve
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