Title :
A Knowledge Engineering System for MEDAS
Author :
Chang, Li-Jen ; Evens, Martha ; Trace, David A.
Author_Institution :
Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL, USA
Abstract :
This paper introduces a Knowledge Engineering System, the Disorder Toolbox (DT), which assists physicians to build, test, and verify the knowledge base for the Medical Emergency Decision Assistance System (MEDAS). DT is designed using a hypertext/hypermedia system and gives physicians an intelligent and user-friendly tool to streamline the disorder pattern creation process. DT reads the Portable Patient File (PPF) generated by the Intelligent Medical Record Entry (IMR-E) System, and allows the medical expert to enter prior and conditional probabilities, and test the posterior probabilities for disorders during the knowledge creation time. After building the disorder patterns, the physician can load a PPF and produce a differential diagnosis using the multimembership Bayesian inference engine. The process of building the Disorder Toolbox and its use are described
Keywords :
Bayes methods; inference mechanisms; knowledge acquisition; medical administrative data processing; Disorder Toolbox; Knowledge Engineering System; MEDAS; Medical Emergency Decision Assistance System; Portable Patient File; conditional probabilities; disorder pattern creation process; intelligent Medical Record Entry; medical expert; multimembership Bayesian inference engine; user-friendly tool; Bayesian methods; Computer science; Expert systems; Knowledge acquisition; Knowledge engineering; Knowledge representation; Medical diagnostic imaging; Medical expert systems; Medical tests; System testing;
Conference_Titel :
Computer-Based Medical Systems, 1994., Proceedings 1994 IEEE Seventh Symposium on
Conference_Location :
Winston-Salem, NC
Print_ISBN :
0-8186-6256-5
DOI :
10.1109/CBMS.1994.315977