PURPOSE: This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. MATERIALS AND METHODS: Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. RESULTS: The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. CONCLUSION The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.

PURPOSE: This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. MATERIALS AND METHODS: Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. RESULTS: The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. CONCLUSION The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.

PURPOSE: This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. MATERIALS AND METHODS: Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. RESULTS: The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. CONCLUSION The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.

PURPOSE: This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. MATERIALS AND METHODS: Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. RESULTS: The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. CONCLUSION The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.

PURPOSE: This study examines the potential of computer-aided design (CAD) systems equipped with artificial intelligence (AI) in reducing the workload of dental technicians. We aimed to compare the accuracy and design time of crowns designed using conventional CAD with those designed using AI-equipped CAD. MATERIALS AND METHODS: Abutment tooth models of a maxillary right second premolar (FDI classification #15) and a maxillary left first molar (FDI classification #26) were mounted on a dental model to form the master model. Stereolithography data were acquired using an intraoral scanner, and five dental technicians designed one crown each for #15 and #26 using both conventional and AI-equipped CAD systems. With the #15 and #26 crowns, six measuring points were established for comparing the accuracy of the occlusal surfaces and design time of the crowns designed by the two CAD systems. The occlusal surfaces were also compared for the buccal and palatal sides. RESULTS: The accuracy of the occlusal surface was 275.5 ± 116.8 µm and 25.7 ± 13 µm for the conventional CAD and AI-equipped CAD systems, respectively. For the buccal and palatal surface comparisons, the conventional CAD system revealed larger misfits on the palatal side for both #15 and #26, with significant differences observed. No significant differences were noted with the AI-equipped CAD system. The AI-equipped CAD resulted in significantly faster design time for both #15 and #26. CONCLUSION The AI-based CAD system significantly reduced design time and enabled the fabrication of uniform crowns regardless of the dental technician's experience and skill.