AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Clavicle

Showing 1 to 10 of 13 articles

Clear Filters

Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

Pediatric radiology
BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. Prior studies have used infant birth-related clavicle fractures as a surrogate to develop a framework...

Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle.

PloS one
In this study, we present a deep learning model for fracture classification on shoulder radiographs using a convolutional neural network (CNN). The primary aim was to evaluate the classification performance of the CNN for proximal humeral fractures (...

Automated localization of the medial clavicular epiphyseal cartilages using an object detection network: a step towards deep learning-based forensic age assessment.

International journal of legal medicine
BACKGROUND: Deep learning is a promising technique to improve radiological age assessment. However, expensive manual annotation by experts poses a bottleneck for creating large datasets to appropriately train deep neural networks. We propose an objec...

Sex determination using the clavicle by deep learning in a Thai population.

Medicine, science, and the law
Determining sex is a critical process in estimating biological profiles from skeletal remains. The clavicle is interesting in studying sex determination because it is durable to the environment, slow to decay, challenging to destroy, making the clavi...

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

International journal of legal medicine
The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the perf...

Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach.

PloS one
This study aimed to develop image-analysis-based classification models for distinguishing individuals younger and older than 30 using the medial clavicle. We extracted 2D images of the medial clavicle from multi-slice computed tomography (MSCT) scans...

Enhancing semantic segmentation in chest X-ray images through image preprocessing: ps-KDE for pixel-wise substitution by kernel density estimation.

PloS one
BACKGROUND: In medical imaging, the integration of deep-learning-based semantic segmentation algorithms with preprocessing techniques can reduce the need for human annotation and advance disease classification. Among established preprocessing techniq...

Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning.

International journal of legal medicine
BACKGROUND: Radiological age assessment using reference studies is inherently limited in accuracy due to a finite number of assignable skeletal maturation stages. To overcome this limitation, we present a deep learning approach for continuous age ass...

No code machine learning: validating the approach on use-case for classifying clavicle fractures.

Clinical imaging
PURPOSE: We created an infrastructure for no code machine learning (NML) platform for non-programming physicians to create NML model. We tested the platform by creating an NML model for classifying radiographs for the presence and absence of clavicle...

Age estimation using medial clavicle by histomorphometry method with artificial intelligence: A review.

Medicine, science, and the law
This review research critically assesses the evolving landscape of age estimation methodologies, with a particular focus on the innovative integration of histomorphometry and artificial intelligence (AI) in the analysis of the medial clavicle. The me...