Publication: Web based health recommender system using rough sets, survival analysis and rule-based expert systems
Issued Date
2007-12-01
Resource Type
ISSN
16113349
03029743
03029743
Other identifier(s)
2-s2.0-38049031650
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Mahidol University
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SCOPUS
Bibliographic Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.4482 LNAI, (2007), 491-499
Suggested Citation
Puntip Pattaraintakorn, Gregory M. Zaverucha, Nick Cercone Web based health recommender system using rough sets, survival analysis and rule-based expert systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol.4482 LNAI, (2007), 491-499. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/24393
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Title
Web based health recommender system using rough sets, survival analysis and rule-based expert systems
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Abstract
We propose a health recommendation system architecture using rough sets, survival analysis approaches and rule-based expert systems. Our main goal is to recommend clinical examinations for patients or physicians from patients' self reported data. Such data will be treated as condition attributes, while survival time from a follow-up study will be treated as the target function. We have amalgamated rough set theory, relational databases, statistics, soft computing and several pertinent techniques to generate a hybrid intelligent system for survival analysis. This study represents the completion of our system by adding a recommendation module. © Springer-Verlag Berlin Heidelberg 2007.