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Shoulder Dislocation

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Detecting upper extremity native joint dislocations using deep learning: A multicenter study.

Clinical imaging
OBJECTIVE: Joint dislocations are orthopedic emergencies that require prompt intervention. Automatic identification of these injuries could help improve timely patient care because diagnostic delays increase the difficulty of reduction. In this study...

Glenoid segmentation from computed tomography scans based on a 2-stage deep learning model for glenoid bone loss evaluation.

Journal of shoulder and elbow surgery
BACKGROUND: The best-fitting circle drawn by computed tomography (CT) reconstruction of the en face view of the glenoid bone to measure the bone defect is widely used in clinical application. However, there are still some limitations in practical app...

Design and Preliminary Evaluation of a Novel Robotic System for Anterior Shoulder Reduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Shoulder dislocations are the most common dislocations and there is a demand for a novel traction device for reducing anterior shoulder dislocations, which can be handled easily without a need for sedation or prolonged observation and recovery. Hence...

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...