An innovative way for mining clinical and administrative healthcare data

Siu Hung Keith Lo, Maiga Chang

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

Abstract

A novel method of "predicting" sitter case attribute value is presented in this paper. The method allows users to choose two attributes, seed and target attribute, and to predict the target attribute value of the forthcoming sitter case. The method first retrieves string sequences of the seed attribute according to filters the users set. Then, it finds the words in the sequences and calculates the term frequencies of the words. With the term frequencies, the proposed method uses vector space model to measure the similarity between the testing sequences and the benchmark sequence. At the end, the testing sequence which has highest Cosine similarity value is chosen and the filtering value the method uses to generate the testing sequence is the predicted result. These predicted results allow hospitals to adjust their strategies on resource assignments to better handle patient needs.

Original languageEnglish
Title of host publicationActive Media Technology - 8th International Conference, AMT 2012, Proceedings
Pages528-533
Number of pages6
DOIs
Publication statusPublished - 2012
Event8th International Conference on Active Media Technology, AMT 2012 - Macau, China
Duration: 4 Dec. 20127 Dec. 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7669 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Active Media Technology, AMT 2012
Country/TerritoryChina
CityMacau
Period4/12/127/12/12

Keywords

  • Data Mining
  • Healthcare
  • Hospital Networks
  • Regular Expression
  • Sitter

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