自然语言处理与临床数据的表示
Natural language processing and the representation of clinical data.
作者信息
Sager N, Lyman M, Bucknall C, Nhan N, Tick L J
机构信息
Courant Institute of Mathematical Sciences, New York University, NY 10012, USA.
出版信息
J Am Med Inform Assoc. 1994 Mar-Apr;1(2):142-60. doi: 10.1136/jamia.1994.95236145.
OBJECTIVE
Develop a representation of clinical observations and actions and a method of processing free-text patient documents to facilitate applications such as quality assurance.
DESIGN
The Linguistic String Project (LSP) system of New York University utilizes syntactic analysis, augmented by a sublanguage grammar and an information structure that are specific to the clinical narrative, to map free-text documents into a database for querying.
MEASUREMENTS
Information precision (I-P) and information recall (I-R) were measured for queries for the presence of 13 asthma-health-care quality assurance criteria in a database generated from 59 discharge letters.
RESULTS
I-P, using counts of major errors only, was 95.7% for the 28-letter training set and 98.6% for the 31-letter test set. I-R, using counts of major omissions only, was 93.9% for the training set and 92.5% for the test set.
目的
建立临床观察与行动的表示形式以及处理自由文本患者文档的方法，以促进诸如质量保证等应用。
设计
纽约大学的语言字符串项目（LSP）系统利用句法分析，并辅以临床叙述特有的子语言语法和信息结构，将自由文本文档映射到数据库中进行查询。
测量
在由59封出院信生成的数据库中，针对13项哮喘医疗质量保证标准的存在情况进行查询，测量信息精度（I-P）和信息召回率（I-R）。
结果
仅使用主要错误计数时，28封信的训练集的I-P为95.7%，31封信的测试集的I-P为98.6%。仅使用主要遗漏计数时，训练集的I-R为93.9%，测试集的I-R为92.5%。
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