ArticleScientific reports2022
Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 4 of them syntheses that pooled it.
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Who cites it
40 citing papers in PubMed, 4 syntheses or guidelines pooled it, 111 citations in OpenAlex.
- Deep learning-based evaluation of panoramic radiographs for osteoporosis screening: a systematic review and meta-analysis.BMC medical imaging · 2025Pooled it
- Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Pooled it
- Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.Journal of bone and mineral metabolism · 2024Pooled it
- Panoramic imaging errors in machine learning model development: a systematic review.Dento maxillo facial radiology · 2024Pooled it
- Establishment of artificial intelligence-driven fluorescence morphometry reveals involvement of osteocyte perilacunar remodeling specifically in mandibular bone of ovariectomized rats.Microscopy (Oxford, England) · 2026Article
- Validation of a deep learning model for bone fragility detection from conventional radiographs: an international cohort study.EClinicalMedicine · 2026Article
- Consensus statement on the application of artificial intelligence in osteoporosis screening and management: perspectives from the Asia-Pacific region.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- Artificial Intelligence in Rheumatology: From Algorithms to Clinical Impact in Osteoporosis and Chronic Inflammatory Rheumatic Diseases.Journal of clinical medicine · 2026Article
- Article
- Artificial Intelligence for Osteoporosis Diagnosis, Risk Prediction and Therapy: Current Advances, Clinical Challenges, and Future Perspectives.Clinical interventions in aging · 2026Review
- Artificial Intelligence and Machine Learning in the Diagnosis and Management of Osteoporosis: A Comprehensive Review.Medicina (Kaunas, Lithuania) · 2025Review
- An exploratory study of explainable deep learning for predicting bone mineral density using clavicle features on chest radiographs: A multi-task approach with regression and segmentation.Journal of applied clinical medical physics · 2025Article
- Deep‑learning based osteoporosis classification in knee X‑rays using transfer‑learning approach.Scientific reports · 2025Article
- Artificial intelligence system for predicting areal bone mineral density from plain X-rays.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Article
- The mTOR signaling pathway mediates the phenotypic switch between adipocytes and osteocytes in mice with obesity-related osteoporosis.European journal of medical research · 2025Article
- Article
- Deep learning algorithm for identifying osteopenia/osteoporosis using cervical radiography.Scientific reports · 2025Article
- Automatic detection of orthodontically induced external root resorption based on deep convolutional neural networks using CBCT images.Scientific reports · 2025Article
- Vision transformer and deep learning based weighted ensemble model for automated spine fracture type identification with GAN generated CT images.Scientific reports · 2025Article
- Reply on "Dental panoramic radiographs by dental students versus artificial intelligence".Osteoporosis and sarcopenia · 2025Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful. In this study, we investigate the use of deep learning to classify osteoporosis from dental panoramic radiographs. In addition, the effect of adding clinical covariate data to the radiographic images on the identification performance was assessed. For objective labeling, a dataset containing 778 images was collected from patients who underwent both skeletal-bone-mineral density measurement and dental panoramic radiography at a single general hospital between 2014 and 2020. Osteoporosis was assessed from the dental panoramic radiographs using convolutional neural network (CNN) models, including EfficientNet-b0, -b3, and -b7 and ResNet-18, -50, and -152. An ensemble model was also constructed with clinical covariates added to each CNN. The ensemble model exhibited improved performance on all metrics for all CNNs, especially accuracy and AUC. The results show that deep learning using CNN can accurately classify osteoporosis from dental panoramic radiographs. Furthermore, it was shown that the accuracy can be improved using an ensemble model with patient covariates.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.