混淆
计算机科学
牙科
目视检查
再现性
医学
人工智能
病理
数学
统计
作者
Jan Kühnisch,Inka Goddon,Susanne Berger,H Senkel,Katharina Bücher,Thomas Oehme,Reinhard Hickel,Roswitha Heinrich‐Weltzien
标识
DOI:10.3390/ijerph6092500
摘要
Given the limitations of adjunct caries detection and diagnostic tools, e.g., imperfect validity and reproducibility, as well as the difficulties in controlling all possible confounding factors, the need for an objective visual caries detection and diagnosis system has become evident. Our work has therefore aimed at systematizing caries lesions with the Universal Visual Scoring System (UniViSS) for occlusal and smooth surface lesions, which can be used for primary and permanent teeth, as well as under clinical, epidemiological, public health and laboratory conditions. Besides the description of the development and methodology of UniViSS, it is shown that UniViSS allows an accurate and reproducible classification of caries lesions on occlusal surfaces.
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