Artificial Intelligence in Dentistry—Narrative Review

Ossowska, Agata; Kusiak, Aida; Świetlik, Dariusz

doi:10.3390/ijerph19063449

Cited by 83 publications

(62 citation statements)

References 52 publications

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“…In endodontics, artificial intelligence is gaining more relevance [ 14 ]. Its significance in endodontic treatment planning and disease diagnosis is growing at the moment [ 15 ].…”

Section: Reviewmentioning

confidence: 99%

Artificial Intelligence in Dentistry: Past, Present, and Future

Agrawal¹,

Nikhade²

2022

Cureus

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Artificial intelligence (AI) has remarkably increased its presence and significance in a wide range of sectors, including dentistry. It can mimic the intelligence of humans to undertake complex predictions and decisionmaking in the healthcare sector, particularly in endodontics. The models of AI, such as convolutional neural networks and/or artificial neural networks, have shown a variety of applications in endodontics, including studying the anatomy of the root canal system, forecasting the viability of stem cells of the dental pulp, measuring working lengths, pinpointing root fractures and periapical lesions and forecasting the success of retreatment procedures. Future applications of this technology were considered in relation to scheduling, patient care, drug-drug interactions, prognostic diagnosis, and robotic endodontic surgery. In endodontics, in terms of disease detection, evaluation, and prediction, AI has demonstrated accuracy and precision. AI can aid in the advancement of endodontic diagnosis and therapy, which can enhance endodontic treatment results. However, before incorporating AI models into routine clinical operations, it is still important to further certify the cost-effectiveness, dependability, and applicability of these models.

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“…In endodontics, artificial intelligence is gaining more relevance [ 14 ]. Its significance in endodontic treatment planning and disease diagnosis is growing at the moment [ 15 ].…”

Section: Reviewmentioning

confidence: 99%

Artificial Intelligence in Dentistry: Past, Present, and Future

Agrawal¹,

Nikhade²

2022

Cureus

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“…Artificial intelligence (AI) is gaining importance in the fields of medicine and dentistry nowadays [ 13 ]. It can be useful in a variety of situations where new technologies might benefit and help people.…”

Section: Methodsmentioning

confidence: 99%

“…The input layer is where information enters the system, and the hidden layer is where the data are processed (where the system decides what to do). NNs may outline any input to output given a set of mathematical models if there is enough data, a lot of data [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Progression of Periodontitis with the Use of Neural Networks

Ossowska

Kusiak

Świetlik

2022

JCM

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Periodontitis is an inflammatory disease of the tissues surrounding the tooth that results in loss of periodontal attachment detected as clinical attachment loss (CAL). The mildest form of periodontal disease is gingivitis, which is a necessary condition for periodontitis development. We can distinguish also some modifying factors which have an influence on the rate of development of periodontitis from which the most important are smoking and poorly controlled diabetes. According to the new classification from 2017, we can identify four stages of periodontitis and three grades of periodontitis. Grades tell us about the periodontitis progression risk and may be helpful in treatment planning and motivating the patients. Artificial neural networks (ANN) are widely used in medicine and in dentistry as an additional tool to support clinicians in their work. In this paper, ANN was used to assess grades of periodontitis in the group of patients. Gender, age, nicotinism approximal plaque index (API), bleeding on probing (BoP), clinical attachment loss (CAL), and pocket depth (PD) were taken into consideration. There were no statistically significant differences in the clinical periodontal assessment in relation to the neural network assessment. Based on the definition of the sensitivity and specificity in medicine we obtained 85.7% and 80.0% as a correctly diagnosed and excluded disease, respectively. The quality of the neural network, defined as the percentage of correctly classified patients according to the grade of periodontitis was 84.2% for the training set. The percentage of incorrectly classified patients according to the grade of periodontitis was 15.8%. Artificial neural networks may be useful tool in everyday dental practice to assess the risk of periodontitis development however more studies are needed.

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“…Recently, various valuable narrative reviews were published that concluded that the AI approach to imaging technology is profoundly changing the established protocols of diagnosis in dentistry [ 4 , 5 , 26 , 62 , 63 , 64 ]. The application of AI in healthcare is an area of significant attention and importance.…”

Section: Introductionmentioning

confidence: 99%

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

et al. 2022

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This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

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Artificial Intelligence in Dentistry—Narrative Review

Cited by 83 publications

References 52 publications

Artificial Intelligence in Dentistry: Past, Present, and Future

Artificial Intelligence in Dentistry: Past, Present, and Future

Evaluation of the Progression of Periodontitis with the Use of Neural Networks

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

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