AI Medical Compendium Topic

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Prosthesis Failure

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Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms.

The bone & joint journal
AIMS: The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance.

Trabeculae microstructure parameters serve as effective predictors for marginal bone loss of dental implant in the mandible.

Scientific reports
Marginal bone loss (MBL) is one of the leading causes of dental implant failure. This study aimed to investigate the feasibility of machine learning (ML) algorithms based on trabeculae microstructure parameters to predict the occurrence of severe MBL...

Hip arthroplasty dislocation risk calculator: evaluation of one million primary implants and twenty-five thousand dislocations with deep learning artificial intelligence in a systematic review of reviews.

International orthopaedics
PURPOSE: This paper aims to provide an overview of the possibility regarding the artificial intelligence application in orthopaedics to predict dislocation with a calculator according to the type of implant (hemiarthroplasty, standard total hip arthr...

Artificial intelligence and machine learning as a viable solution for hip implant failure diagnosis-Review of literature and in vitro case study.

Medical & biological engineering & computing
The digital health industry is experiencing fast-paced research which can provide digital care programs and technologies to enhance the competence of healthcare delivery. Orthopedic literature also confirms the applicability of artificial intelligenc...

Combining deep learning and machine learning for the automatic identification of hip prosthesis failure: Development, validation and explainability analysis.

International journal of medical informatics
AIM: Revision hip arthroplasty has a less favorable outcome than primary total hip arthroplasty and an understanding of the timing of total hip arthroplasty failure may be helpful. The aim of this study is to develop a combined deep learning (DL) and...

Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Clinical orthopaedics and related research
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...

Hip prosthesis failure prediction through radiological deep sequence learning.

International journal of medical informatics
BACKGROUND: Existing deep learning studies for the automated detection of hip prosthesis failure only consider the last available radiographic image. However, using longitudinal data is thought to improve the prediction, by combining temporal and spa...

AI classification of knee prostheses from plain radiographs and real-world applications.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
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 ...