AIMC Topic: Joint Instability

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Automated radiography assessment of ankle joint instability using deep learning.

Scientific reports
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...

Innovative diagnostic framework for shoulder instability: a narrative review on machine learning-enhanced scapular dyskinesis assessment in sports injuries.

European journal of medical research
A common shoulder problem that significantly detracts from patients' quality of life is shoulder instability (SI). Abnormal scapular positioning and movement are closely associated with rotator cuff injuries and SI, as shown by several studies. The a...

Patellar tilt calculation utilizing artificial intelligence on CT knee imaging.

The Knee
BACKGROUND: In the diagnosis of patellar instability, three-dimensional (3D) imaging enables measurement of a wide range of metrics. However, measuring these metrics can be time-consuming and prone to error due to conducting 2D measurements on 3D obj...

A machine learning approach using gait parameters to cluster TKA subjects into stable and unstable joints for discovery analysis.

The Knee
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...

Factors contributing to chronic ankle instability in parcel delivery workers based on machine learning techniques.

BMC medical informatics and decision making
BACKGROUND: Ankle injuries in parcel delivery workers (PDWs) are most often caused by trips. Ankle sprains have high recurrence rates and are associated with chronic ankle instability (CAI). This study aimed to develop, determine, and compare the pre...

Stress radiography of medial knee instability provides a reliable correlation with the severity of injury and medial joint space opening-A robotic biomechanical cadaveric study.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The medial collateral ligament (MCL), and posterior oblique ligament (POL) are the primary valgus stabilisers of the knee, and clinical examinations in grading valgus instability can be inherently subjective. Stress radiography of medial-sid...

Machine learning for classifying chronic ankle instability based on ankle strength, range of motion, postural control and anatomical deformities in delivery service workers with a history of lateral ankle sprains.

Musculoskeletal science & practice
OBJECTIVE: Chronic ankle instability (CAI) frequently develops as a result of lateral ankle sprains (LAS) in delivery service workers (DSWs). Identifying risk factors for CAI is crucial for implementing targeted interventions. This study aimed to dev...

A machine learning approach to stratify patients with hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders according to disorders of gut brain interaction, comorbidities and quality of life.

Neurogastroenterology and motility
BACKGROUND: A high prevalence of disorders of gut-brain interaction (DGBI) exist in patients with hypermobile Ehlers-Danlos Syndrome (hEDS) and hypermobility spectrum disorders (HSD). However, it is unknown if clusters of hEDS/HSD patients exist whic...

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
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...

Methodology and development of a machine learning probability calculator: Data heterogeneity limits ability to predict recurrence after arthroscopic Bankart repair.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The aim of this study was to develop and train a machine learning (ML) algorithm to create a clinical decision support tool (i.e., ML-driven probability calculator) to be used in clinical practice to estimate recurrence rates following an ar...