AIMC Topic: Arthroplasty, Replacement, Knee
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Fully automated workflow for designing patient-specific orthopaedic implants: Application to total knee arthroplasty.
PloS one
Jun 25, 2025
Background Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to treat joint osteoarthritis, reducing pain and improving mobility. Nevertheless, a significant share ...
Accuracy of machine learning in identifying candidates for total knee arthroplasty (TKA) surgery: a systematic review and meta-analysis.
European journal of medical research
Apr 22, 2025
BACKGROUND: The application of machine learning (ML) in predicting the requirement for total knee arthroplasty (TKA) at knee osteoarthritis (KOA) patients has been acknowledged. Nonetheless, the variables employed in the development of ML models are ...
Posttraumatic Arthritis After Anterior Cruciate Ligament Injury: Machine Learning Comparison Between Surgery and Nonoperative Management.
The American journal of sports medicine
Mar 13, 2025
BACKGROUND: Nonoperative and operative management techniques after anterior cruciate ligament (ACL) injury are both appropriate treatment options for selected patients. However, the subsequent development of posttraumatic knee osteoarthritis (PTOA) r...
A machine learning approach using gait parameters to cluster TKA subjects into stable and unstable joints for discovery analysis.
The Knee
Mar 11, 2025
BACKGROUND: Patient-reported joint instability after total knee arthroplasty (TKA) is difficult to quantify objectively. Here, we apply machine learning to cluster TKA subjects using nine literature-proposed gait parameters as knee instability predic...
Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors.
BMC musculoskeletal disorders
Mar 11, 2025
BACKGROUND: Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative risk prediction and assessment tools are lacking in Asia. This study developed the first machine lea...
AI classification of knee prostheses from plain radiographs and real-world applications.
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Mar 11, 2025
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...
An AI-based system for fully automated knee alignment assessment in standard AP knee radiographs.
The Knee
Mar 3, 2025
BACKGROUND: Accurate assessment of knee alignment in pre- and post-operative radiographs is crucial for knee arthroplasty planning and evaluation. Current methods rely on manual alignment assessment, which is time-consuming and error-prone. This stud...
Leveraging machine learning for duration of surgery prediction in knee and hip arthroplasty - a development and validation study.
BMC medical informatics and decision making
Mar 3, 2025
BACKGROUND: Duration of surgery (DOS) varies substantially for patients with hip and knee arthroplasty (HA/KA) and is a major risk factor for adverse events. We therefore aimed (1) to identify whether machine learning can predict DOS in HA/KA patient...
Artificial intelligence and machine learning in knee arthroplasty.
The Knee
Feb 28, 2025
BACKGROUND: Artificial intelligence (AI) and its subset, machine learning (ML), have significantly impacted clinical medicine, particularly in knee arthroplasty (KA). These technologies utilize algorithms for tasks such as predictive analytics and im...
Managing class imbalance in the training of a large language model to predict patient selection for total knee arthroplasty: Results from the Artificial intelligence to Revolutionise the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project.
The Knee
Feb 28, 2025
INTRODUCTION: This study set out to test the efficacy of different techniques used to manage to class imbalance, a type of data bias, in application of a large language model (LLM) to predict patient selection for total knee arthroplasty (TKA).
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