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Monitor: an expert system that validates and interprets time-dependent partial data based on a cystic fibrosis home monitoring program

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4 Author(s)
Slagle, J.R. ; Dept. of Comput. Sci., Minnesota Univ., Minneapolis, MN, USA ; Finkelstein, S.M. ; Leung, L.A. ; Warwick, W.J.

The use of health diaries to monitor patients with chronic diseases has often been complicated by difficulties encountered in data quality assurance and interpretation. An expert system, Monitor, has been developed to predict the health status of cystic fibrosis patients based on daily home measurements of pulse, respiratory rate, weight, inspired vital capacity, and a checklist of symptoms of acute illness. This system ensures data reliability beyond what can be achieved in most current automatic error detection procedures by validating inputs against patient-specific expectations. Its explicit representation of the time dimension and the hierarchical structure of its knowledge base facilitate the abstraction of trends and relationships among the time-dependent data. Dynamically imposed expectations also lend flexibility to the interpretation process by allowing the processing of partial (incomplete) data. Monitor correctly classified 86% (three-category classification) and 94% (two category classification) of 111 cases.

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Biomedical Engineering, IEEE Transactions on  (Volume:36 ,  Issue: 5 )