An inductive algorithm approach to knowledge acquisition for expert system development: a pilot study.
Knowledge acquisition, which consists of knowledge elicitation and knowledge representation, often is considered the weakest link in the design of expert systems. Systems frequently are built on the knowledge of one expert and require extensive use of knowledge engineering techniques to elicit this...
| Publicado en: | Computers in Nursing Vol. 13; no. 5; pp. 226 - 233 |
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| Autor principal: | |
| Formato: | research Journal Article |
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Lippincott Williams & Wilkins
1995 Sep-Oct
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107428801&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 107428801 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 07368593 47P jtl: Computers in Nursing issn: 07368593 maglogo: N pubinfo: dt: 1995 Sep-Oct vid: 13 iid: 5 pid: 433 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 107428801 107428801 1995036683 NLM7585305 107428801 ppf: 226 ppct: 7 formats: tig: atl: An inductive algorithm approach to knowledge acquisition for expert system development: a pilot study. aug: au: Henry SB affil: Box 0608, University of California, San Francisco, San Francisco, CA 94143-0608 sug: subj: Expert Systems Nursing Knowledge Algorithms Software Design Pilot Studies Descriptive Research Comparative Studies Mortality Pneumonia, Pneumocystis Diagnosis Pneumonia, Pneumocystis Prognosis Validity Knowledge Human ab: Knowledge acquisition, which consists of knowledge elicitation and knowledge representation, often is considered the weakest link in the design of expert systems. Systems frequently are built on the knowledge of one expert and require extensive use of knowledge engineering techniques to elicit this knowledge from the expert. Inductive algorithms are a potential alternative method of knowledge acquisition for expert system development. The aim of this pilot study was to examine the feasibility of applying machine learning techniques, specifically, inductive algorithms, to an existing research database as a method for knowledge elicitation and knowledge representation for expert system development. Two inductive algorithms (C4 and Classification and Regression Trees [CART]) that generate decision trees were selected for the analysis using a data set of 201 patients hospitalized for Pneumocystis carinii pneumonia. Neither C4 nor CART produced trees with an accuracy that was significantly better than the baseline accuracy (71.3%) for prediction of outcome in the data set. The mean accuracy of the C4 decision trees was below baseline and the mean accuracy of CART decision trees was 74.6%. The experts found both algorithms comprehensible, but not adequate, and identified important missing predictor variables. The study findings suggest that additional research is needed to examine the appropriate use of inductive algorithms in the transformation of nursing data and information into nursing knowledge. pubtype: Periodical doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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