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Artificial intelligence may help detect proximal caries on bitewing x-ray, reveals study
![Artificial intelligence may help detect proximal caries on bitewing x-ray, reveals study Artificial intelligence may help detect proximal caries on bitewing x-ray, reveals study](https://medicaldialogues.in/h-upload/2024/03/26/750x450_235057-78420214040fig7html.webp)
Artificial intelligence may help detect proximal caries on bitewing x-ray, reveals a study published in the BMC Oral Health.
Dental caries diagnosis requires the manual inspection of diagnostic bitewing images of the patient, followed by a visual inspection and probing of the identified dental pieces with potential lesions. Yet the use of artificial intelligence, and in particular deep-learning, has the potential to aid in the diagnosis by providing a quick and informative analysis of the bitewing images. A dataset of 13,887 bitewings from the HUNT4 Oral Health Study were annotated individually by six different experts, and used to train three different object detection deep-learning architectures: RetinaNet (ResNet50), YOLOv5 (M size), and EfficientDet (D0 and D1 sizes). A consensus dataset of 197 images, annotated jointly by the same six dental clinicians, was used for evaluation. A five-fold cross validation scheme was used to evaluate the performance of the AI models.
Results: The trained models show an increase in average precision and F1-score, and decrease of false negative rate, with respect to the dental clinicians. When compared against the dental clinicians, the YOLOv5 model shows the largest improvement, reporting 0.647 mean average precision, 0.548 mean F1-score, and 0.149 mean false negative rate. Whereas the best annotators on each of these metrics reported 0.299, 0.495, and 0.164 respectively. Deep-learning models have shown the potential to assist dental professionals in the diagnosis of caries. Yet, the task remains challenging due to the artifacts natural to the bitewing images.
Reference:
Pérez de Frutos, J., Holden Helland, R., Desai, S. et al. AI-Dentify: deep learning for proximal caries detection on bitewing x-ray - HUNT4 Oral Health Study. BMC Oral Health 24, 344 (2024). https://doi.org/10.1186/s12903-024-04120-0
Dr. Shravani Dali has completed her BDS from Pravara institute of medical sciences, loni. Following which she extensively worked in the healthcare sector for 2+ years. She has been actively involved in writing blogs in field of health and wellness. Currently she is pursuing her Masters of public health-health administration from Tata institute of social sciences. She can be contacted at editorial@medicaldialogues.in.
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: editorial@medicaldialogues.in. Contact no. 011-43720751