Premium
Clinical expert systems versus linear models: Do we really have to choose?
Author(s) -
Schwartz Steven,
Griffin Timothy,
Fox John
Publication year - 1989
Publication title -
behavioral science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 45
eISSN - 1099-1743
pISSN - 0005-7940
DOI - 10.1002/bs.3830340408
Subject(s) - expert system , linear model , scope (computer science) , computer science , linear system , management science , operations research , artificial intelligence , machine learning , industrial engineering , risk analysis (engineering) , mathematics , engineering , business , mathematical analysis , programming language
This article deals with decision subsystems at the level of the organism. In recent years there has been debate as to whether linear models or clinical expert systems make clinical decisions more effectively. Previous articles in this journal have favored linear models. This article argues the opposite case. We show that expert systems are not necessarily more expensive or less accurate than linear models and that, in theory at least, they can perform many tasks that are beyond the scope of linear models. Indeed, while a linear model may serve as a subsystem of a human or computer expert system, an expert system cannot be seen as a subsystem of a linear model. We conclude that clinical expert systems and linear models are not interchangeable and users should not be forced to choose between them.