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Shankargouda Patil, Sarah M. Albogami, Jagadish Hosmani, Sheetal Mujoo, Mona Awad Kamil, Manawar A Mansour, Hina Naim Abdul, Shilpa Bhandi, Shiek S. S. J. Ahmed
Background: Machine learning (ML) is a key component of artificial intelligence (AI). The terms machine learning, artificial intelligence, and deep learning are erroneously used interchangeably as they appear as monolithic nebulous entities. This technology offers immense possibilities and opportunities to advance diagnostics in the field of medicine and dentistry. This necessitates a deep understanding of AI and its essential components, such as machine learning (ML), artificial neural networks (ANN), and deep learning (DP). Aim: This review aims to enlighten clinicians regarding AI and its applications in the diagnosis of oral diseases, along with the prospects and challenges involved. Review results: AI has been used in the diagnosis of various oral diseases, such as dental caries, maxillary sinus diseases, periodontal diseases, salivary gland diseases, TMJ disorders, and oral cancer through clinical data and diagnostic images. Larger data sets would enable AI to predict the occurrence of precancerous conditions. They can aid in population-wide surveillance and decide on referrals to specialists. AI can efficiently detect microfeatures beyond the human eye and augment its predictive power in critical diagnosis. Conclusion: Although studies have recognized the benefit of AI, the use of artificial intelligence and machine learning has not been integrated into routine dentistry. AI is still in the research phase. The coming decade will see immense changes in diagnosis and healthcare built on the back of this research. Clinical significance: This paper reviews the various applications of AI in dentistry and illuminates the shortcomings faced while dealing with AI research and suggests ways to tackle them. Overcoming these pitfalls will aid in integrating AI seamlessly into dentistry.
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Patil, S., Albogami, S. M., Hosmani, J., Mujoo, S., Kamil, M. A., Mansour, M. A., Abdul, H. N., Bhandi, S., & Ahmed, S. S. S. J. (2022). Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls. Diagnostics, 12(5), 1029. https://doi.org/10.3390/diagnostics12051029
Patil, Shankargouda, et al. "Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls." Diagnostics, vol. 12, no. 5, 2022, pp. 1029, https://doi.org/10.3390/diagnostics12051029.
Patil, Shankargouda, Sarah M. Albogami, Jagadish Hosmani, Sheetal Mujoo, Mona Awad Kamil, Manawar A Mansour, Hina Naim Abdul, Shilpa Bhandi, and Shiek S. S. J. Ahmed. "Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls." Diagnostics 12, no. 5 (2022): 1029. https://doi.org/10.3390/diagnostics12051029.
Patil S., Albogami S. M., Hosmani J. [и др.] Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls // Diagnostics. — 2022. — Vol. 12, № 5. — P. 1029. — URL: https://doi.org/10.3390/diagnostics12051029
@article{patil2022artificial,
title = {{Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls}},
author = {Shankargouda Patil and Sarah M. Albogami and Jagadish Hosmani and Sheetal Mujoo and Mona Awad Kamil and Manawar A Mansour and Hina Naim Abdul and Shilpa Bhandi and Shiek S. S. J. Ahmed},
journal = {Diagnostics},
year = {2022},
volume = {12},
number = {5},
pages = {1029},
doi = {10.3390/diagnostics12051029},
url = {https://doi.org/10.3390/diagnostics12051029}
}TY - JOUR AU - Patil, Shankargouda AU - Albogami, Sarah M. AU - Hosmani, Jagadish AU - Mujoo, Sheetal AU - Kamil, Mona Awad AU - Mansour, Manawar A AU - Abdul, Hina Naim AU - Bhandi, Shilpa AU - Ahmed, Shiek S. S. J. TI - Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls JO - Diagnostics VL - 12 IS - 5 SP - 1029 PY - 2022 DA - 2022/04/19 DO - 10.3390/diagnostics12051029 UR - https://doi.org/10.3390/diagnostics12051029 ER -
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