The optimal diagnostic decision sequence

Chih-Lin Chi; W Nick Street

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The optimal diagnostic decision sequence

Conference proceeding

Peer reviewed

The optimal diagnostic decision sequence

Chih-Lin Chi and W Nick Street

AMIA ... Annual Symposium proceedings, Vol.2008, pp.902-902

11/06/2008

PMID: 18998836

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Abstract

We describe a data mining model for constructing an optimal diagnostic sequence that assists cost-effective sequential decisions. We use heuristic search, i.e., hill climbing and genetic algorithms (GAs), and the evaluation function of cost-based Mean Accuracy Gain (cMAG), which is provided by SVM classifiers, to find this optimal sequence. GA can find a good sequence because of the ability to escape from local optima.

Algorithms

United States

Artificial Intelligence

Decision Support Systems, Clinical - organization & administration

Diagnosis, Computer-Assisted - methods

Information Storage and Retrieval - methods

Medical Records Systems, Computerized - organization & administration

Natural Language Processing

Pattern Recognition, Automated - methods

Quality Assurance, Health Care - methods

Details

Title: Subtitle: The optimal diagnostic decision sequence
Creators: Chih-Lin Chi - University of Iowa
W Nick Street
Resource Type: Conference proceeding
Publication Details: AMIA ... Annual Symposium proceedings, Vol.2008, pp.902-902
PMID: 18998836
ISSN: 1942-597X
eISSN: 1942-597X
Language: English
Date published: 11/06/2008
Academic Unit: Bus Admin College; Nursing; Computer Science; Business Analytics
Record Identifier: 9984380556302771

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