Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study

被引:0
|
作者
Wu, Ziqiong [1 ]
Zhang, Chengqi [1 ]
Ye, Xinjian [2 ]
Dai, Yuwei [2 ,3 ]
Zhao, Jing [1 ]
Zhao, Wuyuan [4 ]
Zheng, Yuanna [1 ,5 ]
机构
[1] Zhejiang Chinese Med Univ, Sch Hosp Stomatol, Mail Box 97,Binwen Rd 548, Hangzhou 310053, Peoples R China
[2] Zhejiang Univ, Zhejiang Prov Clin Res Ctr Oral Dis, Key Lab Oral Biomed Res Zhejiang Prov, Canc Ctr,Stomatol Hosp,Sch Stomatol,Sch Med, Hangzhou, Peoples R China
[3] Zhejiang Univ, Affiliated Hosp 1, Sch Med, Dept Oral & Maxillofacial Surg, Hangzhou, Peoples R China
[4] Hangzhou Erran Technol Co Ltd, Hangzhou, Peoples R China
[5] Ningbo Dent Hosp, Ningbo Oral Hlth Res Inst, Ningbo, Peoples R China
关键词
Time efficiency; Morphological accuracy; Crown; Artificial intelligence-powered; Computer-aided;
D O I
10.1016/j.identj.2024.06.023
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Introduction and aims: Artificial intelligence (AI) has been adopted in the field of dental restoration. This study aimed to evaluate the time efficiency and morphological accuracy of crowns designed by two AI-powered software programs in comparison with conventional computer-aided design software. Methods: A total of 33 clinically adapted posterior crowns were involved in the standard group. AI Automate (AA) and AI Dentbird Crown (AD) used two AI-powered design software programs, while the computer-aided experienced and computer-aided novice employed the Exocad DentalCAD software. Time efficiency between the AI-powered groups and computer-aided groups was evaluated by assessing the elapsed time. Morphological accuracy was assessed by means of three-dimensional geometric calculations, with the root-meansquare error compared against the standard group. Statistical analysis was conducted via the Kruskal-Wallis test (a = 0.05). Results: The time efficiency of the AI-powered groups was significantly higher than that of the computer-aided groups (P < .01). Moreover, the working time for both AA and AD groups was only one-quarter of that for the computer-aided novice group. Four groups significantly differed in morphological accuracy for occlusal and distal surfaces (P < .05). The AD group performed lower accuracy than the other three groups on the occlusal surfaces (P < .001) and the computer-aided experienced group was superior to the AA group in terms of accuracy on the distal surfaces (P = .029). However, morphological accuracy showed no significant difference among the four groups for mesial surfaces and margin lines (P > .05). Conclusion: AI-powered software enhanced the efficiency of crown design but failed to excel at morphological accuracy compared with experienced technicians using computer-aided software. AI-powered software requires further research and extensive deep learning to improve the morphological accuracy and stability of the crown design. (c) 2024 The Authors. Published by Elsevier Inc. on behalf of FDI World Dental Federation. (http://creativecommons.org/licenses/by-nc-nd/4.0/)
引用
收藏
页码:127 / 134
页数:8
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