@inproceedings{afd8fc9bff094c43b792bc84fc672cdc,
title = "An innovative way for mining clinical and administrative healthcare data",
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.",
keywords = "Data Mining, Healthcare, Hospital Networks, Regular Expression, Sitter",
author = "Lo, {Siu Hung Keith} and Maiga Chang",
year = "2012",
doi = "10.1007/978-3-642-35236-2_53",
language = "English",
isbn = "9783642352355",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "528--533",
booktitle = "Active Media Technology - 8th International Conference, AMT 2012, Proceedings",
note = "8th International Conference on Active Media Technology, AMT 2012 ; Conference date: 04-12-2012 Through 07-12-2012",
}