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1.
Ann Clin Biochem ; 24 Suppl 1: 5-11, 1987.
Artigo em Inglês | MEDLINE | ID: mdl-3631885

RESUMO

In domains where the types of data which are to be interpreted are relatively constrained (as in the case of specific laboratory test results), our modular data-driven approach can be very productive and well received by the clinical recipient of the data. The computer rarely surpasses the knowledge of an experts result from lack of communication, imperfect memory, oversight or multiple decision-makers caring for the same patient. In such cases, most of the alerts are immediately recognized as valid, so the need for elaborate explanations is not a high priority. On the other hand, a non-specialist is alerted to the need for additional investigation, tests or collaborative support, by the fact that a reminder or diagnosis that s/he had not previously considered, appears. In other words, for the expert, a data-driven system provides unceasing oversight in high-volume low-yielded situations where a small number of mistakes may uncommonly occur for reasons which are not related to the lack of knowledge of the provider. For the non-specialist the system suggests that the patient may have problems in a domain for which the physician needs additional support. In the present state of the art, we do not think that total reliance on the computer-contained knowledge is the ultimate source of this additional support; providing the awareness of the need may be the most important contribution. Once you know that you need help, it is usually obtainable. In a discussion about how computer systems have failed, Friedman and Gustafson made the following observation.(ABSTRACT TRUNCATED AT 250 WORDS)


Assuntos
Sistemas Inteligentes , Laboratórios , Tomada de Decisões Assistida por Computador , Humanos , Farmacêuticos
2.
Stud Health Technol Inform ; 6: 105-12, 1993.
Artigo em Inglês | MEDLINE | ID: mdl-10163801

RESUMO

ASTM subcommittee E31.15 on Health Knowledge Representation was formed to promote standards for defining and sharing health knowledge bases. Its first standard, the Ardan Syntax, is focused on knowledge bases that can be represented as a set of independent modules called Medical Logic Modules (MLMs). The standard is in clinical use and has generated significant interest in industry and academics. The Extensions task group plans to extend the syntax where appropriate, to expand to other types of knowledge bases. The Validation/Verification task group is approaching the enormous problem of evaluating knowledge bases and the process of sharing them.


Assuntos
Inteligência Artificial , Informática Médica/normas , Unified Medical Language System , Sistemas Inteligentes , Humanos , Lógica , Sistemas Computadorizados de Registros Médicos/normas
3.
Artigo em Inglês | MEDLINE | ID: mdl-1482929

RESUMO

A method is presented where medical knowledge modules, written in the Arden Syntax, are used in a decision-support system (DSS). Knowledge modules are, after syntax-checking, translated into the object oriented programming language C++, compiled and linked to the DSS. The object oriented approach together with developed tools, such as knowledge editor and translator, makes it possible to implement the Arden Syntax and to get an efficient, easy-maintained DSS. Work on a prototype shows that this approach has several advantages when building a DSS where medical knowledge is represented in the Arden Syntax.


Assuntos
Inteligência Artificial , Tomada de Decisões Assistida por Computador , Sistemas de Informação Hospitalar , Linguagens de Programação , Software
4.
Comput Biomed Res ; 27(4): 291-324, 1994 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-7956129

RESUMO

The Arden Syntax, a language designed for writing and sharing task-specific knowledge for Medical Logic Modules (MLMs), has been recently accepted as a standard by the ASTM. The syntax is concerned with the critical task of sharing medical knowledge bases across many institutions. Because of the relative lack of agreement on vocabularies and data standards and because of the many other obstacles, the developers of the Arden Syntax took a pragmatic, straightforward approach that has borne fruit in a very short period of time. The syntax provides a vehicle for the health care community to begin sharing, so that we can see what works and what does not work, and we can begin to address the critical obstacles. In designing a language like the Arden Syntax, the authors make many decisions--but the final document gives only the result of these decisions without any explanation. By writing down the rationale behind the design of the syntax, we hope to aid users of the language, implementors of the language, and future designers of new languages.


Assuntos
Inteligência Artificial , Tomada de Decisões Assistida por Computador , Informática Médica/normas , Linguagens de Programação , Sistemas de Informação/normas , Design de Software
5.
Yearb Med Inform ; (1): 259-262, 2001.
Artigo em Inglês | MEDLINE | ID: mdl-27701612
6.
Yearb Med Inform ; (1): 115-120, 1995.
Artigo em Inglês | MEDLINE | ID: mdl-27668777
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