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Applications and Prospects of Artificial Intelligence in Oral Medicine

Author(s)

Chenglu Ruan*, Yirong Zhu, Jianying Xiong

Affiliation(s)

Department of Stomatology, Sanming Integrated Medicine Hospital, Sanming, Fujian, China *Corresponding Author.

Abstract

In the field of dental medicine, there is an increasing exploration of the application of Artificial Intelligence (AI) to enhance the efficiency and accuracy of diagnosing, treating, and preventing oral diseases. This paper primarily investigates the current applications and future prospects of AI in the realm of dental medicine. Its purpose is to delve into the multifaceted utilization of AI in dentistry, spanning dental imaging, macrobiotics, genomics research, treatment planning, and patient management. By depicting AI applications in these domains, the article underscores its potential advantages, such as improving diagnostic accuracy, tailoring personalized treatment plans, and monitoring patient health status. Methodologically, the paper references the use of deep learning-based image recognition systems and AI technology in genomic research, highlighting the diverse applications of AI in dental medicine. Key conclusions emphasize the immense potential of AI in the dental medicine field, offering crucial support in diagnostics, treatment planning, and patient management. However, the article also points out challenges in practical implementation, including data privacy, algorithm interpretability, and clinical validation. Therefore, the paper emphasizes the need to overcome these challenges in the future to achieve a broader and more profound impact of AI in dental medicine.

Keywords

Oral Medicine; Artificial Intelligence; Diagnosis; Personalized Treatment

References

[1] Bouletreau, P., Makaremi, M., Ibrahim, B., et al., Artificial Intelligence: Applications in orthognathic surgery. Journal of Stomatology Oral and Maxillofacial Surgery, 2019. 120 (4): p. 347-354. [2] Chen, Q.M., Y.H. Wang, and J. Shuai, Current status and future prospects of stomatology research. Journal of Zhejiang University-Science B, 2023. 24 (10): p. 853-867. [3] Fawaz, P., P. El Sayegh, and B.V. Vannet, What is the current state of artificial intelligence applications in dentistry and orthodontics? Journal of Stomatology Oral and Maxillofacial Surgery, 2023. 124 (5). [4] Mohaideen, K., Negi, A., Verma, D. K., et al., Applications of artificial intelligence and machine learning in orthognathic surgery: A scoping review. Journal of Stomatology Oral and Maxillofacial Surgery, 2022. 123 (6): p. E962-E972. [5] Orhan, K., Bilgir, E., Bayrakdar, I. S., et al., Evaluation of artificial intelligence for detecting impacted third molars on cone-beam computed tomography scans. Journal of Stomatology Oral and Maxillofacial Surgery, 2021. 122 (4): p. 333-337. [6] Procházka, A., Charvát, J., Vysata, O., et al., Incremental deep learning for reflectivity data recognition in stomatology. Neural Computing & Applications, 2022. 34 (9): p. 7081-7089. [7] Sun, M. L., Liu, Y., Liu, G. M., et al., Application of Machine Learning to Stomatology: A Comprehensive Review. Ieee Access, 2020. 8: p. 184360-184374. [8] Hegde, S., Ajila, V., Zhu, W., et al., Artificial intelligence in early diagnosis and prevention of oral cancer. Asia-Pacific Journal of Oncology Nursing, 2022. 9 (12).  [9] Hung, K. F., Yeung, A. W. K., Bornstein, M. M., et al., Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging. Dentomaxillofacial Radiology, 2023. 52 (1). [10] Ilhan, B., Lin, K., Guneri, P., Wilder-Smith, P., Improving Oral Cancer Outcomes with Imaging and Artificial Intelligence. Journal of Dental Research, 2020. 99 (3): p. 241-248. [11] Khanagar, S. B., Alkadi, L., Alghilan, M. A., Application and Performance of Artificial Intelligence (AI) in Oral Cancer Diagnosis and Prediction Using Histopathological Images: A Systematic Review. Biomedicines, 2023. 11 (6). [12] Oya, K., Kokomoto, K., Nozaki, K. and Toyokawa, Soral squamous cell carcinoma a diagnosis in digitized histological images using convolutional neural network. Journal of Dental Sciences, 2023. 18 (1): p. 322-329. [13] Pereira-Prado, V., Martins-Silveira, F., Sicco, E., Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review. Diagnostics, 2023. 13 (14). [14] Carrillo-Perez, F., Pecho, O. E., Morales, J. C., Applications of artificial intelligence in dentistry: A comprehensive review. Journal of Esthetic and Restorative Dentistry, 2022. 34 (1): p. 259-280. [15] Joda, T. and N.U. Zitzmann, Personalized workflows in reconstructive dentistry-current possibilities and future opportunities. Clinical Oral Investigations, 2022. 26 (6): p. 4283-4290. [16] Schwendicke, F., W. Samek, and J. Krois, Artificial Intelligence in Dentistry: Chances and Challenges. Journal of Dental Research, 2020. 99 (7): p. 769-774. [17] Snider, V., Homsi, K., Kusnoto, B., Effectiveness of AI-driven remote monitoring technology in improving oral hygiene during orthodontic treatment. Orthodontics & Craniofacial Research, 2023.