Artificial intelligence (AI) is a branch of computer science concerned with building smart software or machines capable of performing tasks that typically require human intelligence. We present a protocol for the use of AI to fabricate implant-supported monolithic zirconia crowns (MZCs) cemented on customized hybrid abutments. The study protocol consisted of: (1) intraoral scan of the implant position; (2) design of the individual abutment and temporary crown using computer-aided design (CAD) software; (3) milling of the zirconia abutment and the temporary polymethyl-methacrylate (PMMA) crown, with extraoral cementation of the zirconia abutment on the relative titanium bonding base, to generate an individual hybrid abutment; (4) clinical application of the hybrid abutment and the temporary PMMA crown; (5) intraoral scan of the hybrid abutment; (6) CAD of the final crown with automated margin line design using AI; (7) milling, sintering and characterisation of the final MZC; and (8) clinical application of the MZC. The outcome variables were mathematical (quality of the fabrication of the individual zirconia abutment) and clinical, such as (1) quality of the marginal adaptation, (2) of interproximal contact points and (3) of occlusal contacts, (4) chromatic integration, (5) survival and (6) success of MZCs. A careful statistical analysis was performed. 90 patients (35 males, 55 females; mean age 53.3 ± 13.7 years) restored with 106 implant-supported MZCs were included in the study. The follow-up varied from 6 months to 3 years. The quality of the fabrication of individual hybrid abutments revealed a mean deviation of 44 μm (± 6.3) between the original CAD design of the zirconia abutment, and the mesh of the zirconia abutment captured intraorally at the end of the provisionalization. At the delivery of the MZCs, the marginal adaptation, quality of interproximal and occlusal contacts, and aesthetic integration were excellent. The three-year cumulative survival and success of the MZCs were 99.0% and 91.3%, respectively. AI seems to represent a reliable tool for the restoration of single implants with MZCs cemented on customised hybrid abutments via a full digital workflow. Further studies are needed to confirm these positive results.

中文翻译：

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固定种植体修复中的人工智能：一项对90例患者的下颌中插入的106个种植体支持的整体氧化锆冠的回顾性研究。

人工智能（AI）是计算机科学的一个分支，与构建能够执行通常需要人类智能的任务的智能软件或机器有关。我们提出了一种使用AI来制造胶合在定制混合基台上的植入物支持的整体式氧化锆冠（MZC）的协议。研究方案包括：（1）种植体位置的口腔内扫描；（2）使用计算机辅助设计（CAD）软件设计单个基台和临时牙冠；（3）研磨氧化锆基台和临时的聚甲基丙烯酸甲酯（PMMA）牙冠，并在相对的钛键合基体上进行氧化锆基台的口腔外固结，以产生单个混合基台；（4）混合基台和PMMA临时牙冠的临床应用；（5）混合基台的口腔内扫描；（6）最终冠的CAD，并使用AI进行自动边距线设计；（7）最终MZC的研磨，烧结和表征；（八）MZC的临床应用。结果变量是数学的（单个氧化锆基台的制造质量）和临床变量，例如（1）边缘适应的质量，（2）近邻接触点和（3）咬合接触，（4）色积分，（5）MZC的生存率和（6）成功。进行了仔细的统计分析。该研究包括90例患者（男35例，女55例；平均年龄53.3±13.7岁），接受106例种植体支持的MZC修复。随访时间从6个月到3年不等。单个混合基台的制造质量表明，氧化锆基台的原始CAD设计与模型之间的平均偏差为44μm（±6.3），并在临时化结束时在口腔内捕获氧化锆基台的网孔。在交付MZC时，其边缘适应性，近邻和咬合接触的质量以及美学整合都非常出色。MZC的三年累计生存率和成功率分别为99.0％和91.3％。AI似乎代表了一种可靠的工具，可通过完整的数字化工作流程，用粘合在定制混合基台上的MZC修复单个植入物。需要进一步的研究来确认这些积极的结果。MZC的三年累计生存率和成功率分别为99.0％和91.3％。AI似乎代表了一种可靠的工具，可通过完整的数字化工作流程，用粘合在定制混合基台上的MZC修复单个植入物。需要进一步的研究来确认这些积极的结果。MZC的三年累计生存率和成功率分别为99.0％和91.3％。AI似乎代表了一种可靠的工具，可通过完整的数字化工作流程，用固定在定制混合基台上的MZC修复单个植入物。需要进一步的研究来确认这些积极的结果。