scholarly journals Application-specific issues in natural language interfacer development for a diagnostic expert system

1988 ◽  
Author(s):  
Karen L. Ryan ◽  
Rebecca Root ◽  
Duane Olawsky
Keyword(s):  
Expert System ◽  
Natural Language ◽  
Application Specific

Kraepelin: an expert system for the diagnosis of Obsessive - Compulsive Disorders

1991 ◽  
Vol 6 (4) ◽  
pp. 171-175 ◽  
Author(s):  
M Roca-Bennasar ◽  
A Garcia-Mas ◽  
N Llaneras ◽  
J Blat ◽  
P Roca
Keyword(s):  
Artificial Intelligence ◽  
Differential Diagnosis ◽  
Expert System ◽  
Natural Language ◽  
Personal Computer ◽  
Clinical History ◽  
User Acceptance ◽  
Obsessive Compulsive ◽  
Obsessive Compulsive Disorders ◽  
Compulsive Disorders

SummaryWe present the construction of an expert system (ES) for the diagnosis of Obsessive-Compulsive Disorders (OCD). It concerns an artificial intelligence tool, in Lisp language compatible with any personal computer (PC) with a hard disk. The ES asks the user 50 questions in natural language, on the patient or on a clinical history. It is provided with 115 rules of reasoning. Using single or multivaluate variables, the ES reaches the diagnosis of the Obsessive-Compulsive Disorders or the recommendations of differential diagnosis with related patterns or involucred with obsessive pathology: phobic, affective, schizophrenic and Gilles de la Tourette disorders. Finally, the perspectives for the utilisation of the ES in psychopathology are disscussed, in conjunction with the 2 serious problems created, design difficulty and user acceptance.

A PROLOG-BASED CHINESE EXPERT SYSTEM

1988 ◽  
Vol 02 (01) ◽  
pp. 17-24
Author(s):  
HSU LOKE SOO
Keyword(s):  
Expert System ◽  
Natural Language ◽  
Knowledge Acquisition ◽  
Domain Expert ◽  
Knowledge Engineer ◽  
Knowledge Application ◽  
Design And Implementation ◽  
Expert System Shell ◽  
Natural Language Interface ◽  
Application Module

This paper presents the design and implementation of a Chinese Expert System Shell which is based on a Chinese Prolog interpreter. The system is divided into three parts: the knowledge acquisition module, the knowledge application module and the inference engine. The knowledge engineer defines the syntax of the language to be used by himself and by the users when they interact with the system. The natural language interface is table driven and can be modified easily. The system also caters for the case when the domain expert finds it difficult to articulate the rules, but is able to give examples. An inductive engine is included to extract rules from examples.

BRAINDEX: An Interactive, Knowledge-Based System Supporting Brain Death Diagnosis

1990 ◽  
Vol 29 (03) ◽  
pp. 193-199 ◽  
Author(s):  
G. Schwarz ◽  
R. Grims ◽  
E. Rumpl ◽  
G. Rom ◽  
G. Pfurtscheller ◽  
...  
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Natural Language ◽  
Brain Death ◽  
Knowledge Based System ◽  
Forward Chaining ◽  
Brain Death Diagnosis ◽  
Knowledge Based ◽  
Expert System Shell

AbstractBRAINDEX (Brain-Death Expert System) is an interactive, knowledge-based expert system offering support to physicians in decision making concerning brain death. The physician is given the possibility of communicating in almost natural language and, therefore, in terms with which he is familiar. This updated version of the system is implemented on an IBM-PC/AT with the expert system shell PC-PLUS and consists of about 430 rules. The determination of brain death is realized with backward chaining and for the optional coma-scaling a forward-chaining mechanism is used.

Natural Language Processing Techniques in Requirements Engineering

2011 ◽  
pp. 21-33 ◽  
Author(s):  
A. Egemen Yilmaz ◽  
I. Berk Yilmaz
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Knowledge Bases ◽  
Syntactic Analysis ◽  
Requirement Analysis ◽  
Specific Knowledge ◽  
Crucial Step ◽  
Development Processes ◽  
Processing Techniques ◽  
Application Specific

Requirement analysis is the very first and crucial step in the software development processes. Stating the requirements in a clear manner, not only eases the following steps in the process, but also reduces the number of potential errors. In this chapter, techniques for the improvement of the requirements expressed in the natural language are revisited. These techniques try to check the requirement quality attributes via lexical and syntactic analysis methods sometimes with generic, and sometimes domain and application specific knowledge bases.

Sign in / Sign up

Export Citation Format

Share Document