Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis
Saifeldin, H., Osorio, J., Xi, M., Safwat, B., Khokher, M., Li, S., Ashmawy, M., Shalaby, L., Khela, S., Le, K., Le, S., Wang, D. (2024). Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis. EKB Journal Management System, 33(1), 1-10. doi: 10.21608/asdj.2024.277176.1229
Hatem Saifeldin; Juan Osorio; Mingze Xi; Barbara Safwat; Muhammad Rizwan Khokher; Shenghong Li; Mostafa S Ashmawy; Lobna Shalaby; Samuel Khela; Khoa Le; Sen Le; Dadong Wang. "Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis". EKB Journal Management System, 33, 1, 2024, 1-10. doi: 10.21608/asdj.2024.277176.1229
Saifeldin, H., Osorio, J., Xi, M., Safwat, B., Khokher, M., Li, S., Ashmawy, M., Shalaby, L., Khela, S., Le, K., Le, S., Wang, D. (2024). 'Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis', EKB Journal Management System, 33(1), pp. 1-10. doi: 10.21608/asdj.2024.277176.1229
Saifeldin, H., Osorio, J., Xi, M., Safwat, B., Khokher, M., Li, S., Ashmawy, M., Shalaby, L., Khela, S., Le, K., Le, S., Wang, D. Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis. EKB Journal Management System, 2024; 33(1): 1-10. doi: 10.21608/asdj.2024.277176.1229

Accuracy of Eyes of AI™ Artificial Intelligence Driven Platform for Lateral Cephalometric Analysis

Ain Shams Dental Journal
Article 2, Volume 33, Issue 1, March 2024, Page 1-10  XML PDF (1.89 MB)
Document Type: Original articles
DOI: 10.21608/asdj.2024.277176.1229
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Authors
Hatem Saifeldin email orcid 1; Juan Osorio2; Mingze Xiorcid 3; Barbara Safwat2; Muhammad Rizwan Khokherorcid 3; Shenghong Liorcid 3; Mostafa S Ashmawyorcid 4; Lobna Shalaby1; Samuel Khela5; Khoa Le2; Sen Le2; Dadong Wangorcid 3
1Orthodontic Department, Faculty of Dentistry, Ain Shams University
2Eyes of AI™(EAI), Sydney NSW 2000, Australia
3Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, NSW 2122, Australia
4Oral Radiology Department, Faculty of Dentistry, Ain Shams University
5Dental Biomaterials Department, Faculty of Dentistry, Ain Shams University
Abstract
Abstract
Aim: The objective of this prospective study was to evaluate the accuracy of cephalometric analyses acquired through manual tracing and the Eyes of AITM AI-driven web-based program.
Materials and Methods: This prospective study employed randomization conducted via computer software, with a determined sample size of 150 cases. Inclusion criteria encompassed good quality lateral cephalograms available in both digital and print formats, absence of artifacts that might hinder anatomical point location, and presence of a clear calibration ruler for magnification determination. Exclusion criteria included lateral cephalograms with identifiable motion artifacts, resolution disparity, or insufficient contrast, as well as those exhibiting positional errors indicated by ear rod markers. Each lateral cephalogram underwent tracing and analysis using the manual method, as well as Eyes of AITM software. Following landmark plotting, linear and angular measurements of Steiner, Downs, McNamara, and Jefferson analyses were calculated.
Results: A comparison of thirty-six cephalometric measurements of Steiner, Downs, McNamara, and Jefferson analyses obtained from manual tracing and AI-driven Eyes of AITM revealed a Concordance Correlation Coefficient (CCC) value above 0.76 for all parameters, indicating strong agreement between manual and AI-driven cephalometric measurements. Furthermore, a CCC value exceeding 0.9 was observed for twenty-eight parameters, indicative of very strong agreement.
Conclusion: Automated lateral cephalometric measurements obtained from Eyes of AITM are accurate when compared to manual measurements.
Keywords
Eyes of AI™; Cephalometric analysis; artificial intelligence; orthodontic diagnosis
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