AIMC Topic: Arthroscopy

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Deep learning-assisted detection of meniscus and anterior cruciate ligament combined tears in adult knee magnetic resonance imaging: a crossover study with arthroscopy correlation.

International orthopaedics
AIM: We aimed to compare the diagnostic performance of physicians in the detection of arthroscopically confirmed meniscus and anterior cruciate ligament (ACL) tears on knee magnetic resonance imaging (MRI), with and without assistance from a deep lea...

Predicting the Reparability of Rotator Cuff Tears: Machine Learning and Comparison With Previous Scoring Systems.

The American journal of sports medicine
BACKGROUND: Repair of rotator cuff tear is not always feasible, depending on the severity. Although several studies have investigated factors related to reparability and various methods to predict it, inconsistent scoring methods and a lack of valida...

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...

Artificial Intelligence Models Are Limited in Predicting Clinical Outcomes Following Hip Arthroscopy: A Systematic Review.

JBJS reviews
BACKGROUND: Hip arthroscopy has seen a significant surge in utilization, but complications remain, and optimal functional outcomes are not guaranteed. Artificial intelligence (AI) has emerged as an effective supportive decision-making tool for surgeo...

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
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...

Enhancing wrist arthroscopy: artificial intelligence applications for bone structure recognition using machine learning.

Hand surgery & rehabilitation
INTRODUCTION: Wrist arthroscopy is a rapidly expanding surgical discipline, but has a long and challenging learning curve. One of its difficulties is distinguishing the various anatomical structures during the procedure. Although artificial intellige...

MRI-based automated multitask deep learning system to evaluate supraspinatus tendon injuries.

European radiology
OBJECTIVE: To establish an automated, multitask, MRI-based deep learning system for the detailed evaluation of supraspinatus tendon (SST) injuries.

Preliminary exploration of deep learning-assisted recognition of superior labrum anterior and posterior lesions in shoulder MR arthrography.

International orthopaedics
PURPOSE: MR arthrography (MRA) is the most accurate method for preoperatively diagnosing superior labrum anterior-posterior (SLAP) lesions, but diagnostic results can vary considerably due to factors such as experience. In this study, deep learning w...

Evaluation of a newly designed deep learning-based algorithm for automated assessment of scapholunate distance in wrist radiography as a surrogate parameter for scapholunate ligament rupture and the correlation with arthroscopy.

La Radiologia medica
PURPOSE: Not diagnosed or mistreated scapholunate ligament (SL) tears represent a frequent cause of degenerative wrist arthritis. A newly developed deep learning (DL)-based automated assessment of the SL distance on radiographs may support clinicians...