Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

doi:10.3390/healthcare10112188

. 2022 Oct 31;10(11):2188.

doi: 10.3390/healthcare10112188.

Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

Affiliations

¹ National Centre for Robotics, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
² College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
³ Military College of Signals (MCS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
⁴ Department of Signal Theory and Communications and Telematic Engineering, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.
⁵ Department of Vascular Surgery, University Hospital of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.
⁶ Universidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, Spain.
⁷ Universidad Internacional Iberoamericana, Arecibo, PR 00613, USA.
⁸ Universidade Internacional do Cuanza, Estrada Nacional 250, Bairro Kaluapanda Cuito- Bié, Angola.
⁹ Universidad Internacional Iberoamericana, Campeche 24560, Mexico.
¹⁰ Fundación Universitaria Internacional de Colombia, Calle 39A #19-18 Bogotá D.C, Colombia.
¹¹ Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea.

PMID: 36360529
PMCID: PMC9690084
DOI: 10.3390/healthcare10112188

Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

Anum Fatima et al. Healthcare (Basel). 2022.

. 2022 Oct 31;10(11):2188.

doi: 10.3390/healthcare10112188.

Authors

Affiliations

¹ National Centre for Robotics, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
² College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
³ Military College of Signals (MCS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
⁴ Department of Signal Theory and Communications and Telematic Engineering, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.
⁵ Department of Vascular Surgery, University Hospital of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.
⁶ Universidad Europea del Atlántico, Isabel Torres 21, 39011 Santander, Spain.
⁷ Universidad Internacional Iberoamericana, Arecibo, PR 00613, USA.
⁸ Universidade Internacional do Cuanza, Estrada Nacional 250, Bairro Kaluapanda Cuito- Bié, Angola.
⁹ Universidad Internacional Iberoamericana, Campeche 24560, Mexico.
¹⁰ Fundación Universitaria Internacional de Colombia, Calle 39A #19-18 Bogotá D.C, Colombia.
¹¹ Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea.

PMID: 36360529
PMCID: PMC9690084
DOI: 10.3390/healthcare10112188

Abstract

Artificial intelligence has been widely used in the field of dentistry in recent years. The present study highlights current advances and limitations in integrating artificial intelligence, machine learning, and deep learning in subfields of dentistry including periodontology, endodontics, orthodontics, restorative dentistry, and oral pathology. This article aims to provide a systematic review of current clinical applications of artificial intelligence within different fields of dentistry. The preferred reporting items for systematic reviews (PRISMA) statement was used as a formal guideline for data collection. Data was obtained from research studies for 2009-2022. The analysis included a total of 55 papers from Google Scholar, IEEE, PubMed, and Scopus databases. Results show that artificial intelligence has the potential to improve dental care, disease diagnosis and prognosis, treatment planning, and risk assessment. Finally, this study highlights the limitations of the analyzed studies and provides future directions to improve dental care.

Keywords: artificial intelligence; clinical applications; deep learning; dentistry.

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Conflict of interest statement

The authors declare no conflict of interests.

Figures

**Figure 1**
Relevant data about studies included for synthesis.

**Figure 2**
Applications of AI in different subfields of dentistry.

See this image and copyright information in PMC

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[1] Haykin S. Neural Networks and Learning Machines, 3/E. Pearson Education India; Noida, India: 2009.

[2] Haykin S. Neural Networks and Learning Machines, 3/E. Pearson Education India; Noida, India: 2009.

[3] Basheer I.A., Hajmeer M. Artificial neural networks: Fundamentals, computing, design, and application. J. Microbiol. Methods. 2000;43:3–31. doi: 10.1016/S0167-7012(00)00201-3. - DOI - PubMed

[4] Basheer I.A., Hajmeer M. Artificial neural networks: Fundamentals, computing, design, and application. J. Microbiol. Methods. 2000;43:3–31. doi: 10.1016/S0167-7012(00)00201-3. - DOI - PubMed

[5] Baxt W.G. Application of artificial neural networks to clinical medicine. Lancet. 1995;346:1135–1138. doi: 10.1016/S0140-6736(95)91804-3. - DOI - PubMed

[6] Baxt W.G. Application of artificial neural networks to clinical medicine. Lancet. 1995;346:1135–1138. doi: 10.1016/S0140-6736(95)91804-3. - DOI - PubMed

[7] Jain A.K., Mao J., Mohiuddin K.M. Artificial neural networks: A tutorial. Computer. 1996;29:31–44. doi: 10.1109/2.485891. - DOI

[8] Jain A.K., Mao J., Mohiuddin K.M. Artificial neural networks: A tutorial. Computer. 1996;29:31–44. doi: 10.1109/2.485891. - DOI

[9] Krois J., Ekert T., Meinhold L., Golla T., Kharbot B., Wittemeier A., Dörfer C., Schwendicke F. Deep learning for the radiographic detection of periodontal bone loss. Sci. Rep. 2019;9:8495. doi: 10.1038/s41598-019-44839-3. - DOI - PMC - PubMed

[10] Krois J., Ekert T., Meinhold L., Golla T., Kharbot B., Wittemeier A., Dörfer C., Schwendicke F. Deep learning for the radiographic detection of periodontal bone loss. Sci. Rep. 2019;9:8495. doi: 10.1038/s41598-019-44839-3. - DOI - PMC - PubMed

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Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

Affiliations

Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

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Cited by

References

Grants and funding

LinkOut - more resources

Full Text Sources