AIMC Topic: Joint Dislocations
Clear Filters Showing 1 to 10 of 17 articles
Development and validation of a predictive nomogram for bilateral posterior condylar displacement using cone-beam computed tomography and machine-learning algorithms: a retrospective observational study.
BMC oral health
Jun 5, 2025
BACKGROUND: Temporomandibular disorders (TMDs) are frequently associated with posterior condylar displacement; however, early prediction of this displacement remains a significant challenge. Therefore, in this study, we aimed to develop and evaluate ...
Automated pediatric TMJ articular disk identification and displacement classification in MRI with machine learning.
Journal of dentistry
Feb 13, 2025
OBJECTIVE: To evaluate the performance of an automated two-step model interpreting pediatric temporomandibular joint (TMJ) magnetic resonance imaging (MRI) using artificial intelligence (AI). Using deep learning techniques, the model first automatica...
The Accuracy of Artificial Intelligence Models in Hand/Wrist Fracture and Dislocation Diagnosis: A Systematic Review and Meta-Analysis.
JBJS reviews
Sep 5, 2024
BACKGROUND: Early and accurate diagnosis is critical to preserve function and reduce healthcare costs in patients with hand and wrist injury. As such, artificial intelligence (AI) models have been developed for the purpose of diagnosing fractures thr...
A deep learning-based algorithm for automatic detection of perilunate dislocation in frontal wrist radiographs.
Hand surgery & rehabilitation
Jun 21, 2024
This study proposes a Deep Learning algorithm to automatically detect perilunate dislocation in anteroposterior wrist radiographs. A total of 374 annotated radiographs, 345 normal and 29 pathological, of skeletally mature adolescents and adults aged ...
Automatic Detection of Perilunate and Lunate Dislocations on Wrist Radiographs Using Deep Learning.
Plastic and reconstructive surgery
Jul 17, 2023
Delayed or missed diagnosis of perilunate or lunate dislocations can lead to significant morbidity. Advances in computer vision provide an opportunity to improve diagnostic performance. In this study, a deep learning algorithm was used for detection ...
A Novel Mini-Invasive Technique of Arthroscopic-Assisted Reduction and Robot-Assisted Fixation for Trans-Scaphoid Perilunate Fracture Dislocations.
Orthopaedic surgery
Mar 2, 2023
OBJECTIVE: Perilunate injuries are rare but devastating carpal injuries. The treatment of perilunate injuries remains challenging and contentious. This study aims to describe a novel mini-invasive surgical technique of arthroscopic-assisted reduction...
Detecting hand joint ankylosis and subluxation in radiographic images using deep learning: A step in the development of an automatic radiographic scoring system for joint destruction.
PloS one
Feb 13, 2023
We propose a wrist joint subluxation/ankylosis classification model for an automatic radiographic scoring system for X-ray images. In managing rheumatoid arthritis, the evaluation of joint destruction is important. The modified total Sharp score (mTS...
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
Nov 29, 2022
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...
Detecting upper extremity native joint dislocations using deep learning: A multicenter study.
Clinical imaging
Sep 24, 2022
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...
Assessment of performances of a deep learning algorithm for the detection of limbs and pelvic fractures, dislocations, focal bone lesions, and elbow effusions on trauma X-rays.
European journal of radiology
Jul 22, 2022
PURPOSE: To appraise the performances of an AI trained to detect and localize skeletal lesions and compare them to the routine radiological interpretation.
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823