Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review

Abstract

Evolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral diseases that have demonstrated phenomenal precision and accuracy in their performance. The aim of this systematic review is to report on the diagnostic accuracy and performance of AI-based models designed for detection, diagnosis, and prediction of dental caries (DC). Eminent electronic databases (PubMed, Google scholar, Scopus, Web of science, Embase, Cochrane, Saudi Digital Library) were searched for relevant articles that were published from January 2000 until February 2022. A total of 34 articles that met the selection criteria were critically analyzed based on QUADAS-2 guidelines. The certainty of the evidence of the included studies was assessed using the GRADE approach. AI has been widely applied for prediction of DC, for detection and diagnosis of DC and for classification of DC. These models have demonstrated excellent performance and can be used in clinical practice for enhancing the diagnostic performance, treatment quality and patient outcome and can also be applied to identify patients with a higher risk of developing DC.

Visual Diagnostics of Dental Caries through Deep Learning of Non-Standardised Photographs Using a Hybrid YOLO Ensemble and Transfer Learning Model

“…Application of an ensemble YOLO model and transfer learning in the current study, was able to improve the outcomes drastically, to over 85%. In contrast to existing work performed on caries detection [ 13 ], the current study focuses on images taken from handheld devices, with the justification that underdeveloped regions of emerging economies may not have access to professional imaging equipment. The current study also implemented a blend of object detection classifiers, a model ensemble, test-time augmentation, and multiple transfer learning classifiers, and statistical evaluation through mean average precision, all of which have not been performed in any previous reports documenting AI application in caries diagnostics [ 13 ].…”

“…YOLO uses a single neural network to process the entire image, segmenting it into sections and forecasting bounding boxes and probabilities for each region [ 12 ]. Although several algorithms have been applied in caries diagnostics, YOLO has only been reported for caries diagnostics using radiomic data [ 13 ]. When using radiomics for caries diagnostics in rural populations, the application of AI introduces the model to specialist interpretation [ 14 ], which can be counterintuitive, because the purpose of the model is to aid in areas where specialist consultations are scarce.…”

Use of artificial intelligence software in dental education: A study on assisted proximal caries assessment in bitewing radiographs

“…With regard to radiology training, traditional lecturing can be assisted with case revision. With the introduction of AI in different areas of medicine 20 and dentistry 21–29 as a tool for assisting treatment planning and diagnosis of pathology, it could be speculated that this technology could be valuable in diagnostic dental education. Various computer programs for image analysis have been evaluated previously to assess their potential for caries detection 8,10,12 and one involved third‐year dental students, 13 where application of the AI software was found to improve their ability to detect enamel‐only caries in bitewings.…”

“…With regard to radiology training, traditional lecturing can be assisted with case revision. With the introduction of AI in different areas of medicine 20 and dentistry [21][22][23][24][25][26][27][28][29] as a tool for assisting treatment planning and diagnosis of pathology, it could be speculated that this technology could be valuable in diagnostic dental education.…”

Evaluation of flexural strength of bulk-fill composite resin after immersion in fruit juices: An in vitro study

“…Dental cavities, more commonly referred to as tooth decay, are the corrosion of the surface of tooth enamel due to the combined activity of microorganisms, acids, plaques, and tartar. [ 1 2 ] It needs to be filled with restorative materials as soon as possible to prevent any complications. [ 3 ] Resin-based composites are increasingly employed in dental restorations due to their esthetics.…”