AIMC Topic: Knee Prosthesis
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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 ...
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 ...
TKA-AID: An Uncertainty-Aware Deep Learning Classifier to Identify Total Knee Arthroplasty Implants.
The Journal of arthroplasty
Jan 19, 2025
BACKGROUND: A drastic increase in the volume of primary total knee arthroplasties (TKAs) performed nationwide will inevitably lead to higher volumes of revision TKAs in which the primary knee implant must be removed. An important step in 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...
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...
Evaluation of a novel robotic testing method for stability and kinematics of total knee arthroplasty.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Oct 24, 2024
PURPOSE: This work developed a novel preclinical test of total knee replacements (TKRs) in order to explain TKR instability linked to patient dissatisfaction. It was hypothesized that stability tests on the isolated moving prostheses would provide no...
Development of an artificial intelligence model for predicting implant size in total knee arthroplasty using simple X-ray images.
Journal of orthopaedic surgery and research
Aug 27, 2024
BACKGROUND: Accurate estimation of implant size before surgery is crucial in preparing for total knee arthroplasty. However, this task is time-consuming and labor-intensive. To alleviate this burden on surgeons, we developed a reliable artificial int...
Reliable prediction of implant size and axial alignment in AI-based 3D preoperative planning for total knee arthroplasty.
Scientific reports
Jul 23, 2024
The size and axial alignment of prostheses, when planned during total knee replacement (TKA) are critical for recovery of knee function and improvement of knee pain symptoms. This research aims to study the effect of artificial intelligence (AI)-base...
An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 2, 2024
To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this st...
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