AIMC Topic: Radiography, Dental

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Identification of dental implant systems from low-quality and distorted dental radiographs using AI trained on a large multi-center dataset.

Scientific reports
Most artificial intelligence (AI) studies have attempted to identify dental implant systems (DISs) while excluding low-quality and distorted dental radiographs, limiting their actual clinical use. This study aimed to evaluate the effectiveness of an ...

Identification of Root Canal Morphology in Fused-rooted Mandibular Second Molars From X-ray Images Based on Deep Learning.

Journal of endodontics
INTRODUCTION: Understanding the intricate anatomical morphology of fused-rooted mandibular second molars (MSMs) is essential for root canal treatment. The present study utilized a deep learning approach to identify the three-dimensional root canal mo...

Deep learning for determining the difficulty of endodontic treatment: a pilot study.

BMC oral health
BACKGROUND: To develop and validate a deep learning model for automated assessment of endodontic case difficulty from periapical radiographs.

Conquering class imbalances in deep learning-based segmentation of dental radiographs with different loss functions.

Journal of dentistry
OBJECTIVE: The imbalanced nature of real-world datasets is an ongoing challenge in the field of machine and deep learning. In medicine and in dentistry, most data samples represent patients not affected by pathologies, and on imagery, pathologic imag...

Artificial intelligence in age and sex determination using maxillofacial radiographs: A systematic review.

The Journal of forensic odonto-stomatology
In the past few years, there has been an enormous increase in the application of artificial intelligence and its adoption in multiple fields, including healthcare. Forensic medicine and forensic odontology have tremendous scope for development using ...

Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

Journal of dentistry
OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the car...

Artificial intelligence-assisted full-mouth radiograph mounting in dental education.

Journal of dental education
OBJECTIVES: With the increasing prevalence of artificial intelligence (AI) and the significant research gap in the application of AI within dentistry, this study aimed to (1) evaluate the efficiency and accuracy of dental students in full-mouth radio...

Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review.

BMC oral health
BACKGROUND: The aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the detection of caries lesion (CL).

Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.

Oral radiology
OBJECTIVES: We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis.