AIMC Topic: Radiography
Clear Filters Showing 141 to 150 of 1087 articles
A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI.
Scientific reports
Mar 5, 2024
Breast density, or the amount of fibroglandular tissue (FGT) relative to the overall breast volume, increases the risk of developing breast cancer. Although previous studies have utilized deep learning to assess breast density, the limited public ava...
Teardrop Alignment Changes After Volar Locking Plate Fixation of Distal Radius Fractures With Volar Ulnar Fragments.
Hand (New York, N.Y.)
Mar 4, 2024
BACKGROUND: We assessed factors associated with change in radiographic teardrop angle following volar locking plate (VLP) fixation of volarly displaced intra-articular distal radius fractures with volar ulnar fragments (VUF) within the ICUC database....
Real-world testing of an artificial intelligence algorithm for the analysis of chest X-rays in primary care settings.
Scientific reports
Mar 3, 2024
Interpreting chest X-rays is a complex task, and artificial intelligence algorithms for this purpose are currently being developed. It is important to perform external validations of these algorithms in order to implement them. This study therefore a...
Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.
Clinical oral investigations
Mar 2, 2024
OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aime...
Empirical data drift detection experiments on real-world medical imaging data.
Nature communications
Feb 29, 2024
While it is common to monitor deployed clinical artificial intelligence (AI) models for performance degradation, it is less common for the input data to be monitored for data drift - systemic changes to input distributions. However, when real-time ev...
Deep learning performance compared to healthcare experts in detecting wrist fractures from radiographs: A systematic review and meta-analysis.
European journal of radiology
Feb 27, 2024
OBJECTIVE: To perform a systematic review and meta-analysis of the diagnostic accuracy of deep learning (DL) algorithms in the diagnosis of wrist fractures (WF) on plain wrist radiographs, taking healthcare experts consensus as reference standard.
Performance evaluation of a deep learning model for automatic detection and localization of idiopathic osteosclerosis on dental panoramic radiographs.
Scientific reports
Feb 23, 2024
Idiopathic osteosclerosis (IO) are focal radiopacities of unknown etiology observed in the jaws. These radiopacities are incidentally detected on dental panoramic radiographs taken for other reasons. In this study, we investigated the performance of ...
Deep learning algorithm for automatically measuring Cobb angle in patients with idiopathic scoliosis.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Feb 17, 2024
PURPOSE: The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when ...
Development of a Machine-Learning Model for Anterior Knee Pain After Total Knee Arthroplasty With Patellar Preservation Using Radiological Variables.
The Journal of arthroplasty
Feb 15, 2024
BACKGROUND: Anterior knee pain (AKP) following total knee arthroplasty (TKA) with patellar preservation is a common complication that significantly affects patients' quality of life. This study aimed to develop a machine-learning model to predict the...
A deep learning approach for projection and body-side classification in musculoskeletal radiographs.
European radiology experimental
Feb 14, 2024
BACKGROUND: The growing prevalence of musculoskeletal diseases increases radiologic workload, highlighting the need for optimized workflow management and automated metadata classification systems. We developed a large-scale, well-characterized datase...
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