摘要
一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者从德国Aache N发回的新闻报道，研究表明，“拔牙是最常用的医疗程序之一。拔牙适应症是基于临床和放射检查以及患者个体参数的组合，应该非常小心。”这项研究的财政支持来自亚琛大学。我们的新闻编辑从亚琛大学医院的研究中获得了一句话：“然而，确定是否应该拔牙并不是一个简单的决定。此外，在分析X线片时，视觉和认知缺陷可能会导致错误的决定。人工智能(A I)可以作为决策支持工具，提供拔牙能力的评分。使用26956(PANs),我们训练了一个ResNet50网络,对1184张全景x线片上的单颗牙齿进行分类。为此,我们对牙齿进行了不同边缘的裁剪和注释。在一个测试数据集上评估了基于人工智能的分类方法和牙科医生分类方法的有效性。此外,我们还对基于人工智能的分类方法和牙科医生分类方法进行了比较。最佳AI模型的可解释性通过CAMERS的类激活图显示，最佳AI模型区分值得保存牙齿的ROC-AUC为0.901，边缘为2%，而牙科医生的平均ROC-AUC仅为0.797.，拔牙率为19.1%，AI模型的PR-AUC为0.749.虽然牙科医生的评估只获得了0.589.个人工智能模型，在仅仅基于X射线图像预测牙齿移动方面优于牙科医生/专家，而人工智能的性能随着背景信息的增加而提高。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Aache n, Germany, by NewsRx correspondents, research stated, “Tooth extraction is one of the most frequently performed medical procedures. The indication is based on the combination of clinical and radiological examination and individual patient parameters and should be made with great care.” Financial support for this research came from Universitatsklinikum RWTH Aachen. Our news editors obtained a quote from the research from University Hospital RWT H Aachen, “However, determining whether a tooth should be extracted is not alway s a straightforward decision. Moreover, visual and cognitive pitfalls in the ana lysis of radiographs may lead to incorrect decisions. Artificial intelligence (A I) could be used as a decision support tool to provide a score of tooth extracta bility. Using 26,956 single teeth images from 1,184 panoramic radiographs (PANs) , we trained a ResNet50 network to classify teeth as either extraction-worthy or preservable. For this purpose, teeth were cropped with different margins from P ANs and annotated. The usefulness of the AI-based classification as well that of dentists was evaluated on a test dataset. In addition, the explainability of th e best AI model was visualized via a class activation mapping using CAMERAS. The ROC-AUC for the best AI model to discriminate teeth worthy of preservation was 0.901 with 2% margin on dental images. In contrast, the average RO C-AUC for dentists was only 0.797. With a 19.1% tooth extractions prevalence, the AI model’s PR-AUC was 0.749, while the dentist evaluation only r eached 0.589. AI models outperform dentists/specialists in predicting tooth extr action based solely on X-ray images, while the AI performance improves with incr easing contextual information.”
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