General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Cecilia Xie
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
    • E-mail: editor@ijcte.org
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IJCTE 2010 Vol.2(2): 185-188 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2010.V2.138

Modeling Clinical Database Using Time Series Based Temporal Mining

Akash Rajak and Kanak Saxena

Abstract—Clinical database contains huge amount of information about patients, medical tests and doctor’s prescription. As the result of laboratory test, findings of physical examination and diagnosis are noted during time points or periods, by adding time dimension in clinical database we can retrieve vital information from the database. This paper presents the study of diabetes mellitus type 1 patients on the basis of time series based representation of clinical temporal data.

Index Terms—temporal database, blood glucose level, insulin plasma level, type 1 diabetes mellitus, time series.

Akash Rajak is with the Krishna Institute of Engineering and Technology, Ghaziabad, India (phone: +91-9873718407, e-mail: akashrajak@rediffmail.com, aakash@kiet.edu).
Kanak Saxena is with the Samrat Ashok Technological Institute, Vidisha, India (e-mail: ksv1909@yahoo.com).

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Cite: Akash Rajak and Kanak Saxena, "Modeling Clinical Database Using Time Series Based Temporal Mining," International Journal of Computer Theory and Engineering vol. 2, no. 2, pp. 185-188, 2010.


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