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   -> Volume 7, Issue 5


Answer: Wavelet Transformation in medical diagnosis (WD 7.4 #17)
 
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"Piotr Wojdyllo" (pwoj@cbr.tpsa.pl)
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PostPosted: Thu Apr 23, 1998 3:36 pm    
Subject: Answer: Wavelet Transformation in medical diagnosis (WD 7.4 #17)
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#26 Answer: Wavelet Transformation in medical diagnosis (WD 7.4 #17)

Dear Tang,

I am a Ph.D. student in Institute of Mathematics, Warsaw
University. In my research led in in Group of Mathematical Logic under
direction of prof. A .Skowron I deal with cases of epilepsy. Our
method combines wavelet analysis of EEG with rough set methods. Our
study is concerned now on detection of posttraumatic cases in a group
suffering epilepsy.

Results are the following:

1. Known subjects we can recognize with 100% accuracy and unknown
objects we recognize with sensitivity 71% and specifity 75%. Tests
done on half of population.

2. Known subjects we can recognize with 100% accuracy and unknown
objects we can classify with efficiency 86% and 65% depending of
decision class. Tests done on one excluded subject (Of course,
percentage is a mean value for different subjects).

Extended abstract of my work "Wavelets, rough sets and artificial
neural networks in EEG analysis" will appear soon in Wavelet
Digest. The work will appear in Proceedings of Rough Sets and Current
Trends in Computing Conference, Lecture Notes in Computer Science,
Springer Verlag.

By the way, let me know about projects of using wavelets in medical
diagnosis, especially in EEG analysis, you are aware of or engaged in.

Yours sincerely

Piotr Wojdyllo

Institute of Mathematics
Warsaw University
Banacha 2,
02-097 Warsaw
POLAND
All times are GMT + 1 Hour
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