Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/24518
Title: Intelligent classification techniques for mining temporal patterns from clinical datasets
Researcher: Sethukkarasi, R
Guide(s): Kannan, A
Keywords: Fuzzy Cognitive Map
Genetic Algorithm
Information and communication engineering
Medical diagnosis system
Temporal data
Upload Date: 3-Sep-2014
University: Anna University
Completed Date: 01/09/2013
Abstract: Representation of temporal knowledge and analysis of temporal data are essential for effective temporal reasoning in medical diagnosis systems which are gaining importance recently These temporal representation models provide features for temporal rules extraction through association rule mining which are necessary to perform detective inference in medical expert systems Most of the existing temporal mining systems focus on mining clinical data assumes instant stamping of tuples as the time stamping method In such systems database is created using a series of observations taken at different time points and the mining algorithm classifies newlinethe data based on the time instants recorded in the database How eve the analysis techniques need to consider data performing to a time interval Hence it is necessary to propose new representation and reasoning methods for the effective analysis of medical data newline
Pagination: xx, 194p.
URI: http://hdl.handle.net/10603/24518
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificate.pdf487.03 kBAdobe PDFView/Open
03_abstract.pdf14.28 kBAdobe PDFView/Open
04_acknowledgemnt.pdf7.07 kBAdobe PDFView/Open
05_contents.pdf28.03 kBAdobe PDFView/Open
06_chapter1.pdf126.15 kBAdobe PDFView/Open
07_chapter2.pdf106.84 kBAdobe PDFView/Open
08_chapter3.pdf26.77 kBAdobe PDFView/Open
09_chapter4.pdf89.98 kBAdobe PDFView/Open
10_chapter5.pdf803.27 kBAdobe PDFView/Open
11_chapter6.pdf584.51 kBAdobe PDFView/Open
12_chapter7.pdf14.51 kBAdobe PDFView/Open
13_references.pdf60.49 kBAdobe PDFView/Open
14_publications.pdf8.24 kBAdobe PDFView/Open
15_vitae.pdf5.46 kBAdobe PDFView/Open


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