Title |
Recent dental practices using Artificial Intelligence (AI): A survey
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Authors |
Ekta Gupta1,*, Siddeeq Maysan2, Susmitha Murella3, Anitta Rachel Saju4, Silvi Grover5 & Agrima Vasudeva6
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Affiliation |
1Department of Orthodontics, Siddhpur Dental College & Hospital, Dethali, Patan, Gujarat, India; 2Department of Oral and Maxillofacial Resident Tel-Aviv Sourasky Medical Center, Israel; 3Department of Dental Surgery, General Dentist, Vijaywada, Andhra Pradesh, India; 4Department of Dental Surgery, General practitioner, Kerala, India; 5Department of Dental Surgery, General Dentist, Punjab, India; 6Department of Endodontics, Santosh Dental College, Ghaziabad, Uttar Pradesh, India; *Corresponding author
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Ekta Gupta - E - mail: drektagupta22@gmail.com
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Article Type |
Research Article
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Date |
Received March 1, 2025; Revised March 31, 2025; Accepted March 31, 2025, Published March 31, 2025
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Abstract |
This study investigates the integration of Artificial Intelligence in contemporary dental practices, focusing on its impact and implementation. A structured survey administered to 150 dental professionals evaluates awareness, adoption rates and perceived benefits of artificial intelligence technologies in dentistry. Simulated data reveals emerging trends in artificial intelligence applications, including diagnostic accuracy, treatment planning efficiency and patient management optimization. Findings highlight a growing acceptance of artificial intelligence, noting its potential to enhance diagnostic precision and streamline treatment processes while addressing challenges related to technology integration and practitioner training. This research provides insights into the evolving role of artificial intelligence in dental settings and informs future directions for optimizing artificial intelligence integration in the field. |
Keywords |
Artificial Intelligence (AI), dental practices, diagnostic accuracy, treatment planning, patient management, adoption rates, awareness, technology integration, practitioner training, simulated data, artificial intelligence applications, workflow optimization
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Citation |
Gupta et al. Bioinformation 21(3): 514-521 (2025)
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Edited by |
Neelam Goyal & Shruti Dabi
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ISSN |
0973-2063
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Publisher |
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License |
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
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