Name
Abstract | ||
|---|---|---|
Information overload is a well-known problem for clinicians who must review large amounts of data in patient records. Concept-oriented views, which organize patient data around clinical concepts such as diagnostic strategies and therapeutic goals, may offer a solution to the problem of information overload. However, although concept-oriented views are desirable, they are difficult to create and maintain. We have developed a general-purpose, knowledge-based approach to the generation of concept-oriented views and have developed a system to test our approach. The system creates concept-oriented views through automated identification of relevant patient data. The knowledge in the system is represented by both a semantic network and rules. The key relevant data identification function is accomplished by a rule-based traversal of the semantic network. This paper focuses on the design and implementation of the system; an evaluation of the system is reported separately. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1006/jbin.2001.1013 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
rule based,knowledge base,semantic network,knowledge based system,information overload | Data science,Data mining,Information overload,Tree traversal,Information retrieval,Computer science,Knowledge-based systems,Semantic network,System model | Journal |
Volume | Issue | ISSN |
34 | 2 | 1532-0464 |
Citations | PageRank | References |
12 | 1.84 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qing Zeng | 1 | 547 | 67.98 |
| James J Cimino | 2 | 1109 | 179.01 |