Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study
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....
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | International Dental Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0020653924001965 |
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| author | Ziqiong Wu Chengqi Zhang Xinjian Ye Yuwei Dai Jing Zhao Wuyuan Zhao Yuanna Zheng |
| author_facet | Ziqiong Wu Chengqi Zhang Xinjian Ye Yuwei Dai Jing Zhao Wuyuan Zhao Yuanna Zheng |
| author_sort | Ziqiong Wu |
| collection | DOAJ |
| description | 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-mean-square error compared against the standard group. Statistical analysis was conducted via the Kruskal–Wallis test (α = 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. |
| format | Article |
| id | doaj-art-4d7567d2c7514cb98929ca69ddc31c24 |
| institution | Kabale University |
| issn | 0020-6539 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Dental Journal |
| spelling | doaj-art-4d7567d2c7514cb98929ca69ddc31c242025-01-21T04:12:43ZengElsevierInternational Dental Journal0020-65392025-02-01751127134Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro StudyZiqiong Wu0Chengqi Zhang1Xinjian Ye2Yuwei Dai3Jing Zhao4Wuyuan Zhao5Yuanna Zheng6School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, ChinaStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Centre for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Centre of Zhejiang University, Hangzhou, ChinaStomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Centre for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Centre of Zhejiang University, Hangzhou, China; Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaSchool/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, ChinaHangzhou Erran Technology Co., Ltd., Hangzhou, ChinaSchool/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, China; Ningbo Dental Hospital/Ningbo Oral Health Research Institute, Ningbo, China; Corresponding author. School/Hospital of Stomatology, Zhejiang Chinese Medical University, Mail Box 97, Binwen Road 548, Hangzhou 310053, China; Ningbo Dental Hospital/Ningbo Oral Health Research Institute, Ningbo, China.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-mean-square error compared against the standard group. Statistical analysis was conducted via the Kruskal–Wallis test (α = 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.http://www.sciencedirect.com/science/article/pii/S0020653924001965Time efficiencyMorphological accuracyCrownArtificial intelligence-poweredComputer-aided |
| spellingShingle | Ziqiong Wu Chengqi Zhang Xinjian Ye Yuwei Dai Jing Zhao Wuyuan Zhao Yuanna Zheng Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study International Dental Journal Time efficiency Morphological accuracy Crown Artificial intelligence-powered Computer-aided |
| title | Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study |
| title_full | Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study |
| title_fullStr | Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study |
| title_full_unstemmed | Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study |
| title_short | Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study |
| title_sort | comparison of the efficacy of artificial intelligence powered software in crown design an in vitro study |
| topic | Time efficiency Morphological accuracy Crown Artificial intelligence-powered Computer-aided |
| url | http://www.sciencedirect.com/science/article/pii/S0020653924001965 |
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