Artificial Intelligence in Periodontology: Advantages and Challenges


Abstract views: 168 / PDF downloads: 496

Authors

DOI:

https://doi.org/10.58600/eurjther2211

Keywords:

Artificial Intelligence, Periodontal diseases, Periodontitis

Metrics

Metrics Loading ...

References

Polizzi A, Quinzi V, Lo Giudice A, et al (2024) Accuracy of Artificial Intelligence Models in the Prediction of Periodontitis: A Systematic Review. JDR Clin Trans Res 23800844241232318. https://doi.org/10.1177/23800844241232318

Ahmed N, Abbasi MS, Zuberi F, et al (2021) Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry-A Systematic Review. Biomed Res Int 2021:9751564. https://doi.org/10.1155/2021/9751564

Papapanou PN, Sanz M, Buduneli N, et al (2018) Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Clin Periodontol 45 Suppl 20:S162–S170. https://doi.org/10.1111/jcpe.12946

Ramenzoni LL, Lehner MP, Kaufmann ME, et al (2021) Oral Diagnostic Methods for the Detection of Periodontal Disease. Diagnostics (Basel) 11:571. https://doi.org/10.3390/diagnostics11030571

Chang J, Chang M-F, Angelov N, et al (2022) Application of deep machine learning for the radiographic diagnosis of periodontitis. Clin Oral Investig 26:6629–6637. https://doi.org/10.1007/s00784-022-04617-4

Alotaibi G, Awawdeh M, Farook FF, et al (2022) Artificial intelligence (AI) diagnostic tools: utilizing a convolutional neural network (CNN) to assess periodontal bone level radiographically-a retrospective study. BMC Oral Health 22:399. https://doi.org/10.1186/s12903-022-02436-3

Chen C-C, Wu Y-F, Aung LM, et al (2023) Automatic recognition of teeth and periodontal bone loss measurement in digital radiographs using deep-learning artificial intelligence. J Dent Sci 18:1301–1309. https://doi.org/10.1016/j.jds.2023.03.020

Uzun Saylan BC, Baydar O, Yeşilova E, et al (2023) Assessing the Effectiveness of Artificial Intelligence Models for Detecting Alveolar Bone Loss in Periodontal Disease: A Panoramic Radiograph Study. Diagnostics (Basel) 13:1800. https://doi.org/10.3390/diagnostics13101800

Cholan P, Ramachandran L, Umesh SG, et al (2023) The Impetus of Artificial Intelligence on Periodontal Diagnosis: A Brief Synopsis. Cureus 15:e43583. https://doi.org/10.7759/cureus.43583

Scott J, Biancardi AM, Jones O, Andrew D (2023) Artificial Intelligence in Periodontology: A Scoping Review. Dent J (Basel) 11:43. https://doi.org/10.3390/dj11020043

Tariq A, Nakhi FB, Salah F, et al (2023) Efficiency and accuracy of artificial intelligence in the radiographic detection of periodontal bone loss: A systematic review. Imaging Sci Dent 53:193–198. https://doi.org/10.5624/isd.20230092

Chakravorty S, Aulakh BK, Shil M, et al (2024) Role of Artificial Intelligence (AI) in Dentistry: A Literature Review. J Pharm Bioallied Sci 16:S14–S16. https://doi.org/10.4103/jpbs.jpbs_466_23

Chawla RL, Gadge NP, Ronad S, et al (2023) Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study. Cureus 15:e48309. https://doi.org/10.7759/cureus.48309

Aldakhil S, Alkhurayji K, Albarrak S, et al (2024) Awareness and Approaches Regarding Artificial Intelligence in Dentistry: A Scoping Review. Cureus 16:e51825. https://doi.org/10.7759/cureus.51825

Surlari Z, Budală DG, Lupu CI, et al (2023) Current Progress and Challenges of Using Artificial Intelligence in Clinical Dentistry-A Narrative Review. J Clin Med 12:7378. https://doi.org/10.3390/jcm12237378

Downloads

Published

2024-06-11

How to Cite

Altındal, D. (2024). Artificial Intelligence in Periodontology: Advantages and Challenges. European Journal of Therapeutics, 30(4), 548–550. https://doi.org/10.58600/eurjther2211

Issue

Section

Letter to the Editor

Categories