AIMC Topic: Joint Instability
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Editorial Commentary: Machine Learning and Artificial Intelligence Are Valuable Tools yet Dependent on the Data Input.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Sep 24, 2024
Machine learning is likely to become one of the most valuable tools for predicting outcomes in patients with patellofemoral instability. Traditional statistical analysis is challenging in this diagnosis as the result of the multitude of risk factors....
Machine-Learning Models Reliably Predict Clinical Outcomes in Medial Patellofemoral Ligament Reconstruction.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Aug 10, 2024
PURPOSE: To develop a machine-learning model to predict clinical outcomes after medial patellofemoral ligament reconstruction (MPFLR) and identify the important predictive indicators.
Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Jul 21, 2024
PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. While risk factors for patellofemoral instability, a common paediatric injury, are well-established in adults, data concerning the progression of paed...
GaitNet+ARL: A Deep Learning Algorithm for Interpretable Gait Analysis of Chronic Ankle Instability.
IEEE journal of biomedical and health informatics
Jul 2, 2024
Chronic ankle instability (CAI) is a major public health concern and adversely affects people's mobility and quality of life. Traditional assessment methods are subjective and qualitative by means of clinician observation and patient self-reporting, ...
ChatGPT-4 Performs Clinical Information Retrieval Tasks Using Consistently More Trustworthy Resources Than Does Google Search for Queries Concerning the Latarjet Procedure.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Jun 25, 2024
PURPOSE: To assess the ability of ChatGPT-4, an automated Chatbot powered by artificial intelligence, to answer common patient questions concerning the Latarjet procedure for patients with anterior shoulder instability and compare this performance wi...
Transformer-Based Multilabel Deep Learning Model Is Efficient for Detecting Ankle Lateral and Medial Ligament Injuries on Magnetic Resonance Imaging and Improving Clinicians' Diagnostic Accuracy for Rotational Chronic Ankle Instability.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Jun 12, 2024
PURPOSE: To develop a deep learning (DL) model that can simultaneously detect lateral and medial collateral ligament injuries of the ankle, aiding in the diagnosis of chronic ankle instability (CAI), and assess its impact on clinicians' diagnostic pe...
Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability.
Scientific reports
May 18, 2024
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. T...
Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs.
European radiology
Apr 18, 2024
OBJECTIVES: To develop and validate an artificial intelligence (AI) system for measuring and detecting signs of carpal instability on conventional radiographs.
Knee landmarks detection via deep learning for automatic imaging evaluation of trochlear dysplasia and patellar height.
European radiology
Feb 10, 2024
OBJECTIVES: To develop and validate a deep learning-based approach to automatically measure the patellofemoral instability (PFI) indices related to patellar height and trochlear dysplasia in knee magnetic resonance imaging (MRI) scans.
The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Oct 12, 2023
PURPOSE: Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has shown promising potential for early and reliable detection of i...
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