ArticleInternational journal of legal medicine2024
Machine learning and deep learning enabled age estimation on medial clavicle CT images.
Article in International journal of legal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Pelvic MRI-based machine learning models for age estimation and age threshold classification in living children and young adults.International journal of legal medicine · 2026Article
- Comprehensive assessment of minors' biological profiles using explainable machine learning: the assessment of age, stature, body mass, and sex.International journal of legal medicine · 2026Article
- Forensic age estimation and legal age thresholds classification based on the elbow MRI and data mining in a Chinese population.International journal of legal medicine · 2026Article
- Molecular biology research progress in post-mortem interval (PMI) estimation in forensic medicine.International journal of legal medicine · 2026Review
- Development of an age estimation method for the coxal bone and lumbar vertebrae obtained from post-mortem computed tomography images using a convolutional neural network.International journal of legal medicine · 2026Article
- An X-ray bone age assessment method for hands and wrists of adolescents in Western China based on feature fusion deep learning models.International journal of legal medicine · 2025Article
- Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.International journal of legal medicine · 2025Review
- Age-related patterns in mandibular third molar eruption: presenting new forensic age assessment reference data from a Chinese population.Forensic science, medicine, and pathology · 2025Article
- Automatic maxillary sinus segmentation and age estimation model for the northwestern Chinese Han population.BMC oral health · 2025Article
- Bone Age Assessment Using Various Medical Imaging Techniques Enhanced by Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Review
- A probability model for estimating age in young individuals relative to key legal thresholds: 15, 18 or 21-year.International journal of legal medicine · 2025Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
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 performance on normal and variant clavicles. This study retrospectively collected 1049 patients (mean± SD: 22.50±4.34 years) and split them into normal training and test sets, and variant training and test sets. An additional 53 variant clavicles were incorporated into the variant test set. The development stages of normal MCE were used to build a linear model and support vector machine (SVM) for BAE. The CT slices of MCE were automatically segmented and used to train DL models for automated BAE. Comparisons were performed by linear versus ML versus DL, and normal versus variant clavicles. Mean absolute error (MAE) and classification accuracy was the primary parameter of comparison. For BAE, the SVM had the best MAE of 1.73 years, followed by the commonly-used CNNs (1.77-1.93 years), the linear model (1.94 years), and the hybrid neural network CoAt Net (2.01 years). In DL models, SE Net 18 was the best-performing DL model with similar results to SVM in the normal test set and achieved an MAE of 2.08 years in the external variant test. For age classification, all the models exhibit superior performance in the classification of 18-, 20-, 21-, and 22-year thresholds with limited value in the 16-year threshold. Both ML and DL models produce desirable performance in BAE based on medial clavicle CT.
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