NDLI: Spirometric data analysis by support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Khubani, Jitendra Mhetre, Manisha R.
Copyright Year	2012
Description	Author affiliation: Dept. of Instrumentation and Control Engg, VIT, Pune-411037, Maharashtra, India (Khubani, Jitendra; Mhetre, Manisha R.)
Abstract	A spirometer is an apparatus for measuring the volume of air inspired and expired by the lungs. Spirometry is one of the most widely applied clinical tests in respiratory medicine to diagnose obstructive and to rule out restrictive pulmonary diseases. In this work, attempt has been made to predict pattern recognition accuracy using support vector regression in order to enhance the spirometric investigations. Support vector machine constructs a hyperplane or set of hyperplanes in a high-or infinite- dimensional space, which can be used for classification, regression, or other tasks. We have collected data from different hospitals. The acquired data are then used to predict pattern recognition accuracy. Since this method is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording. We applied the SVM to construct the prediction model and select Polynomial Function as the kernel function.
Starting Page	121
Ending Page	124
File Size	657782
Page Count	4
File Format	PDF
ISBN	9781467310406
e-ISBN	9781467310437
DOI	10.1109/ISPTS.2012.6260897
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-07
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spirometry Pattern Recognition accuracy Pattern recognition MATLAB Training Accuracy FVC Restrictive lung disease Support vector machine classification Obstructive lung disease Support vector regression FEV1 Kernel
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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