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THE SYSTEM FOR NEUROLOGICAL ANALYSIS OF PATIENT SYMPTOMS: AN INTEGRATED ARTIFICIAL INTELLIGENCE PROTOTYPE

机译:患者症状的神经病学分析系统:一种集成的人工智能原型

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Objectives: To create a stroke expert system prototype that reads a patient text file, computes a disease location, and presents brain graphics showing the lesion. Methods: Coded in Common Lisp, The Natural Language Module reads a text file, parses, and produces parse trees. An Information Extraction Module employs rules to extract data from parse trees and to store these into a database. A Neuro-Anatomic Atlas has been created to represent clinically relevant nervous system structures. A Localization Module employs rules and methods to map from a clinical finding to an anatomic structure. The Graphics Module presents representations of brain structures corresponding to the localization. A 3D Brain Model has been created by scanning a specimen and is a part of this module. Results: Text files representing stroke syndromes are analyzed by the system which produces localization hypotheses and graphical representations of the structures. Formal controlled trials of program behavior are planned. Conclusions: The prototype demonstrates feasibility and should, as new knowledge is incorporated, evolve into a utility for diagnosis, instruction, and experimentation. Formal testing will be required in later stages of the project.
机译:目标:创建一个中风专家系统原型,该原型可以读取患者文本文件,计算疾病位置并显示显示病变的脑部图形。方法:自然语言模块使用Common Lisp进行编码,读取一个文本文件,进行解析,并生成解析树。信息提取模块采用规则从解析树中提取数据并将其存储到数据库中。已经创建了神经解剖图谱来代表临床相关的神经系统结构。定位模块采用规则和方法将临床发现映射到解剖结构。图形模块提供了与定位相对应的大脑结构的表示。通过扫描样本创建了3D脑模型,该模型是该模块的一部分。结果:代表中风综合征的文本文件由系统进行分析,该系统产生定位假设和结构的图形表示。计划对程序行为进行正式的对照试验。结论:该原型演示了可行性,并且随着新知识的加入,该原型应发展成为用于诊断,指导和实验的实用工具。在项目的后期阶段将需要正式测试。

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