Title |
AI driven monitoring of orthodontic tooth movement using automated image analysis
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Authors |
Chetan Dilip Patil1, Aameer Fazluddin Parkar1,*, Snehal Bhalerao1, Pradeep Kawale1, Anshuj Ajay Rao Thetay1 & Seema Lahoti2
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Affiliation |
1Department of Orthodontics and Dentofacial Orthopedics, Yogita Dental College and hospital, Khed, Ratnagiri, Maharashtra, India; 2Department of Orthodontics and Dentofacial Orthopedics, RKDF Dental College and Research Centre, Bhopal, Madhya Pradesh, India; *Corresponding author
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Chetan Dilip Patil - E - mail: drchetan1@yahoo.co.in
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Article Type |
Research Article
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Date |
Received February 1, 2025; Revised February 28, 2025; Accepted February 28, 2025, Published February 28, 2025
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Abstract |
Artificial intelligence (AI) driven automated image analysis accurately tracks orthodontic tooth movement by reducing reliance on time-consuming manual assessments. AI achieved 92% precision with a 0.25 mm error margin and a strong correlation (r = 0.94, p < 0.001) to manual measurements in a study of 100 patients. AI analysis took 3 seconds per image set, significantly faster than the 7-minute manual process (p < 0.001). Orthodontists rated AI reliability at 4.7/5, with 86% preferring AI-assisted monitoring. Thus, AI enhances treatment efficiency, standardization, and clinical decision-making. |
Keywords |
Artificial intelligence, orthodontic tooth movement, automated image analysis, deep learning, intraoral photographs, AI in orthodontics
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Citation |
Patil et al. Bioinformation 21(2): 173-176 (2025)
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Edited by |
Hiroj Bagde MDS, (PhD), PGDCR, PGDHHM, PGDL, PGDM
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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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