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Digitization (automation) of production stages with Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) technologies has led to a digital revolution in dentistry, as in many other fields of the industry. In current dentistry, the digitalization process can be defined as direct and indirect workflow. The clinical reliability and success of the indirect digital workflow made possible by these technologies have been proven by scientific studies. With the development of intraoral scanners (IOS), a virtual model is obtained by direct digitalization. This method eliminated the conventıonale impression and dental cast model steps required for indirect digitalization. Intraoral scanners are used as an alternative to convantıonal impressions in single and short edentulous cases. It has already been emphasized that direct digitalization is a reliable alternative to the conventional impression method, as the clinical applicability, accuracy, and precision of the manufactured restorations have been scientifically verified. Therefore, the clinical use of direct digitalization is increasing (exponentially) day by day, and new upgraded versions of software, along with various modifications for the hardware equipment, are being developed. Integrating artificial intelligence (AI) supported software into the intraoral scanning process can be seen as the beginning of a new era for direct digitalization. Therefore the aim of this study is to evaluate the effect of artificial intelligence on the scanning time, the amount of data collected, and the image accuracy obtained.
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It was planned intraoral scanning (3Shape TRIOS A/S, Copenhagen, Denmark) of the participants' mandible (n=21) with artificial intelligence (AI on) and without artificial intelligence (AI off). Reference equilateral triangles for scanning were digitally designed and produced with a 3D printer. Then these triangles bonded to the buccal surfaces of #34, #44, and the lingual surfaces of #36#46 teeth. The lower jaw of each participant was scanned by the same operator, in line with the recommended scanning protocol. Furthermore, scanning was performed randomly, with AI on and off.
The IOS software automatically recorded the data required for quantitative comparing the scanning time and the obtained images (TRIOS Scanning Version 1.18.310, 3Shape A/S). In order to compare the scanning effectiveness between the methods, the area data of the digital images of the triangular objects obtained during both scans were calculated in a computer environment with reverse engineering software (Geomagic design X version 2016.1.0, 3D Systems Inc. Rock Hill, SC).
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21 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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