Chen Ling, Morrey C Paul, Gu Huanying, Halper Michael, Perl Yehoshua
Department of Science, BMCC, City University of New York, New York, NY, USA.
J Am Med Inform Assoc. 2009 Jan-Feb;16(1):116-31. doi: 10.1197/jamia.M2604. Epub 2008 Oct 24.
Chemical concepts assigned multiple "Chemical Viewed Structurally" semantic types (STs) in the Unified Medical Language System (UMLS) are subject to ambiguous interpretation. The multiple assignments may denote the fact that a specific represented chemical (combination) is a conjugate, derived via a chemical reaction of chemicals of the different types, or a complex, composed of a mixture of such chemicals. The previously introduced Refined Semantic Network (RSN) is modified to properly model these varied multi-typed chemical combinations.
The RSN was previously introduced as an enhanced abstraction of the UMLS's concepts. It features new types, called intersection semantic types (ISTs), each of which explicitly captures a unique combination of ST assignments in one abstract unit. The ambiguous ISTs of different "Chemical Viewed Structurally" ISTs of the RSN are replaced with two varieties of new types, called conjugate types and complex types, which explicitly denote the nature of the chemical interactions. Additional semantic relationships help further refine that new portion of the RSN rooted at the ST "Chemical Viewed Structurally."
The number of new conjugate and complex types and the amount of changes to the type assignment of chemical concepts are presented.
The modified RSN, consisting of 35 types and featuring 22 new conjugate and complex types, is presented. A total of 800 (about 98%) chemical concepts representing multi-typed chemical combinations from "Chemical Viewed Structurally" STs are uniquely assigned one of the new types. An additional benefit is the identification of a number of illegal ISTs and ST assignment errors, some of which are direct violations of exclusion rules defined by the UMLS Semantic Network.
The modified RSN provides an enhanced abstract view of the UMLS's chemical content. Its array of conjugate and complex types provides a more accurate model of the variety of combinations involving chemicals viewed structurally. This framework will help streamline the process of type assignments for such chemical concepts and improve user orientation to the richness of the chemical content of the UMLS.
在统一医学语言系统（UMLS）中，被赋予多种“结构视角下的化学物质”语义类型（STs）的化学概念容易产生歧义性解释。多种赋值可能表明一个特定的代表性化学物质（组合）是共轭物，通过不同类型化学物质的化学反应衍生而来，或者是复合物，由这些化学物质的混合物组成。对先前引入的精炼语义网络（RSN）进行修改，以恰当地对这些多样的多类型化学组合进行建模。
RSN先前作为UMLS概念的增强抽象被引入。它具有新的类型，称为交集语义类型（ISTs），每个IST在一个抽象单元中明确捕获ST赋值的唯一组合。RSN中不同“结构视角下的化学物质”ISTs的歧义性ISTs被两种新类型取代，称为共轭类型和复合类型，它们明确表示化学相互作用的性质。额外的语义关系有助于进一步细化RSN中以ST“结构视角下的化学物质”为根的新部分。
给出了新的共轭和复合类型的数量以及化学概念类型赋值的变化量。
展示了修改后的RSN，它由35种类型组成，具有22种新的共轭和复合类型。总共800个（约98%）代表来自“结构视角下的化学物质”STs的多类型化学组合的化学概念被唯一地赋予一种新类型。另一个好处是识别出一些非法的ISTs和ST赋值错误，其中一些直接违反了UMLS语义网络定义的排除规则。
修改后的RSN提供了UMLS化学内容的增强抽象视图。其共轭和复合类型阵列提供了一个更准确的模型，用于表示从结构角度来看涉及化学物质的各种组合。这个框架将有助于简化此类化学概念的类型赋值过程，并改善用户对UMLS化学内容丰富性的导向。
