AIMC Topic: Arthroplasty, Replacement, Knee
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Deep learning-based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data.
Annals of the rheumatic diseases
Feb 12, 2025
OBJECTIVES: Primary knee osteoarthritis (KOA) is a heterogeneous disease with clinical and molecular contributors. Biofluids contain microRNAs and metabolites that can be measured by omic technologies. Multimodal deep learning is adept at uncovering ...
Biopsychosocial based machine learning models predict patient improvement after total knee arthroplasty.
Scientific reports
Feb 10, 2025
Total knee arthroplasty (TKA) is an effective treatment for end stage osteoarthritis. However, biopsychosocial features are not routinely considered in TKA clinical decision-making, despite increasing evidence to support their role in patient recover...
A Workflow-Efficient Approach to Pre- and Post-Operative Assessment of Weight-Bearing Three-Dimensional Knee Kinematics.
The Journal of arthroplasty
Feb 6, 2025
BACKGROUND: Knee kinematics during daily activities reflect disease severity preoperatively and are associated with clinical outcomes after total knee arthroplasty (TKA). It is widely believed that measured kinematics would be useful for preoperative...
Novel dilation-erosion labeling technique allows for rapid, accurate and adjustable alignment measurements in primary TKA.
Computers in biology and medicine
Dec 16, 2024
BACKGROUND: Optimal implant position and alignment remains a controversial, yet critical topic in primary total knee arthroplasty (TKA). Future study of ideal implant position will require the ability to efficiently measure component positions at sca...
Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.
Medical & biological engineering & computing
Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
Machine learning is better than surgeons at assessing unicompartmental knee replacement radiographs.
The Knee
Nov 30, 2024
BACKGROUND: Poor results occasionally occur after unicompartmental knee replacement (UKR). It is often difficult, even for experienced surgeons, to determine why patients have poor outcomes from radiographs. The aim was to compare the ability of expe...
Artificial intelligence-based analysis of lower limb muscle mass and fatty degeneration in patients with knee osteoarthritis and its correlation with Knee Society Score.
International journal of computer assisted radiology and surgery
Nov 3, 2024
PURPOSE: Lower-limb muscle mass reduction and fatty degeneration develop in patients with knee osteoarthritis (KOA) and could affect their symptoms, satisfaction, expectation and functional activities. The Knee Society Scoring System (KSS) includes p...
Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.
The Journal of arthroplasty
Oct 29, 2024
BACKGROUND: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardwar...
Utilization of Machine Learning Models to More Accurately Predict Case Duration in Primary Total Joint Arthroplasty.
The Journal of arthroplasty
Oct 28, 2024
BACKGROUND: Accurate operative scheduling is essential for the appropriation of operating room esources. We sought to implement a machine learning model to predict primary total hip arthroplasty (THA) and total knee arthroplasty (TKA) case time.
Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty.
The Journal of arthroplasty
Oct 20, 2024
BACKGROUND: While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated in previous studies, their performance in racial and ethnic minority patients has not been investigat...
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