The Journal of forensic odonto-stomatology
Apr 30, 2024
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 ...
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...
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...
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).
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.
INTRODUCTION: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different ...
There is a growing trend of artificial intelligence (AI) applications in veterinary medicine, with the potential to assist veterinarians in clinical decisions. A commercially available, AI-based software program (AISP) for detecting common radiograph...
STATEMENT OF PROBLEM: With the growing importance of implant brand detection in clinical practice, the accuracy of machine learning algorithms in implant brand detection has become a subject of research interest. Recent studies have shown promising r...
OBJECTIVES: This systematic review on generative adversarial network (GAN) architectures for dental image analysis provides a comprehensive overview to readers regarding current GAN trends in dental imagery and potential future applications.
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