Demystifying artificial intelligence and deep learning in dentistry

Abstract

Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, capturing its intrinsic statistical patterns and structures. Neural networks (NNs) have been increasingly employed for ML complex data. The application of multilayered NN is referred to as "deep learning", which has been recently investigated in dentistry. Convolutional neural networks (CNNs) are mainly used for processing large and complex imagery data, as they are able to extract image features like edges, corners, shapes, and macroscopic patterns using layers of filters. CNN algorithms allow to perform tasks like image classification, object detection and segmentation. The literature involving AI in dentistry has increased rapidly, so a methodological guidance for designing, conducting and reporting studies must be rigorously followed, including the improvement of datasets. The limited interaction between the dental field and the technical disciplines, however, remains a hurdle for applicable dental AI. Similarly, dental users must understand why and how AI applications work and decide to appraise their decisions critically. Generalizable and robust AI applications will eventually prove helpful for clinicians and patients alike.

Analysis of Deep Learning Techniques for Dental Informatics: A Systematic Literature Review

“…Even though this research provided an excellent literature review of dental disorders and applications, they should have covered more DL-related topics. The majority of the review studies [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ] dentistry primarily focused on classic ML methods or generic artificial neural networks (ANNs), when feature extraction for diagnosis is required [ 35 ], and where feature extraction is involved for diagnosis. They could not address emerging DL architectures on dental disease diagnosis, such as generative adversarial networks (GANs) [ 36 ], extreme learning machines (ELMs) [ 37 ], or graph convolutional networks (GCNs) [ 38 , 39 ], etc.…”

Optimized Adversarial Network with Faster Residual Deep Learning for Osteoarthritis Classification in Panoramic Radiography

“…Many innovations in the AI paradigm have presented different algorithms for examining X-ray scans [15]. Convolutional neural network (CNN) technology was proven for many purposes like extracting particular sections of X-ray scans and detecting abnormalities [16][17][18][19][20]. Various researches on dental X-ray image analysis have been undertaken, including tooth discovery by panoramic image analysis, osteoporosis analysis, and sinusitis analysis.…”

Artificial Intelligence in Dentistry: Literature Review

“…The idea of a machine being capable of doing human tasks is known as artificial intelligence [1,2]. Artificial intelligence has been developing since 1943 [1].…”

“…Artificial intelligence has been developing since 1943 [1]. In the health care system, artificial intelligence has successfully been incorporated for data collection and mammograms for breast cancer screening [2]. It has assisted doctors in the fields of ophthalmology, dermatology, and radiology [3].…”

“…Narrow artificial intelligence cannot make complex decisions such as treatment plans, and medicine prescriptions like humans. However, artificial intelligence augments human decision power [2]. Artificial intelligence is at its optimum ability and still improving day by day.…”