目的:为了评估质量,临床验收,时间效率,以及新型人工智能(AI)驱动工具的一致性,用于自动进行单颗牙齿置换的术前植入计划,与基于人类智能(HI)的方法相比。
方法:为了验证一种新颖的AI驱动的植入物放置工具,纳入了之前获得的10个时间匹配锥形束计算机断层扫描(CBCT)扫描和口内扫描(IOS)的数据集,这些数据集用于单个下颌磨牙/前磨牙植入.将用于植入物计划的AI预训练模型与基于人类专家的计划进行了比较,其次是出口,评估和比较两种通用植入物-人工智能生成和人类生成-对于每种情况。两种方法的质量由12名校准牙医通过盲法观察使用视觉模拟量表(VAS)进行评估,而临床接受度是通过AI与HI战斗(图灵测试)进行评估的。随后,对两种规划方法的时间效率和一致性进行了评估和比较。
结果:总体而言,收集了360次观察,240专用于VAS,其中95%(AI)和96%(HI)不需要专业,临床相关校正。在AI与HI图灵测试(120个观察)中,4例AI和HI判断匹配,AI在3中受到青睐,HI在3中受到青睐。此外,AI完成计划的速度是HI的两倍多,只需198±33秒,而435±92秒(p<0.05)。此外,与HI(MSD=0.3±0.17mm)相比,AI在零度中值表面偏差(MSD)方面表现出更高的一致性。
结论:人工智能证明了专家质量和临床可接受的单种植计划,证明比基于HI的方法更具时效性和一致性。
结论:术前植入计划通常需要经验丰富的专家之间的多学科合作,可能很复杂,繁琐且耗时。然而,人工智能驱动的植入计划有可能允许临床上可接受的计划,明显比人类专家更有时间效率和一致性。
OBJECTIVE: To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated presurgical implant planning for single tooth replacement, compared to a human intelligence (HI)-based approach.
METHODS: To validate a novel AI-driven implant placement tool, a dataset of 10 time-matching cone beam computed tomography (CBCT) scans and intra-oral scans (IOS) previously acquired for single mandibular molar/premolar implant placement was included. An AI pre-trained model for implant planning was compared to human expert-based planning, followed by the export, evaluation and comparison of two generic implants-AI-generated and human-generated-for each case. The quality of both approaches was assessed by 12 calibrated dentists through blinded observations using a visual analogue scale (VAS), while clinical acceptance was evaluated through an AI versus HI battle (Turing test). Subsequently, time efficiency and consistency were evaluated and compared between both planning methods.
RESULTS: Overall, 360 observations were gathered, with 240 dedicated to VAS, of which 95 % (AI) and 96 % (HI) required no major, clinically relevant corrections. In the AI versus HI Turing test (120 observations), 4 cases had matching judgments for AI and HI, with AI favoured in 3 and HI in 3. Additionally, AI completed planning more than twice as fast as HI, taking only 198 ± 33 s compared to 435 ± 92 s (p < 0.05). Furthermore, AI demonstrated higher consistency with zero-degree median surface deviation (MSD) compared to HI (MSD=0.3 ± 0.17 mm).
CONCLUSIONS: AI demonstrated expert-quality and clinically acceptable single-implant planning, proving to be more time-efficient and consistent than the HI-based approach.
CONCLUSIONS: Presurgical implant planning often requires multidisciplinary collaboration between highly experienced specialists, which can be complex, cumbersome and time-consuming. However, AI-driven implant planning has the potential to allow clinically acceptable planning, significantly more time-efficient and consistent than the human expert.