TY - JOUR
T1 - Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools
T2 - application of PROTÉGÉ-II to protocol-based decision support
AU - Tu, Samson W.
AU - Eriksson, Henrik
AU - Gennari, John H.
AU - Shahar, Yuval
AU - Musen, Mark A.
N1 - Funding Information:
This work has been supportedi n part by grantsL M05157 and LM05208 from the National Library of Medicine, by grant HS06330f rom the Agency for Health Care Policy and Research,a nd by gifts from Digital Equipment Corporation and the Computer-BasedA ssessmentP roject of American Board of Family Practice. Dr. Musen is the recipient of U.S. National ScienceF oundationYoung Investigator Award IRI-9257578.
PY - 1995/1/1
Y1 - 1995/1/1
N2 - PROTÉGÉ-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTÉGÉ-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTÉGÉ-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTÉGÉ-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.
AB - PROTÉGÉ-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTÉGÉ-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTÉGÉ-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTÉGÉ-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.
KW - Decision support
KW - Expert systems
KW - Knowledge acquisition
UR - http://www.scopus.com/inward/record.url?scp=0029311031&partnerID=8YFLogxK
U2 - 10.1016/0933-3657(95)00006-R
DO - 10.1016/0933-3657(95)00006-R
M3 - Article
AN - SCOPUS:0029311031
SN - 0933-3657
VL - 7
SP - 257
EP - 289
JO - Artificial Intelligence in Medicine
JF - Artificial Intelligence in Medicine
IS - 3
ER -