A comparative study on chronic obstructive pulmonary and pneumonia diseases diagnosis using neural networks and artificial immune system.

Abstract:

:Millions of people are diagnosed every year with a chest disease in the world. Chronic obstructive pulmonary and pneumonia diseases are two of the most important chest diseases. And these are very common illnesses in Turkey. In this paper, a comparative study on chronic obstructive pulmonary and pneumonia diseases diagnosis was realized by using neural networks and artificial immune systems. For this purpose, three different neural networks structures and one artificial immune system were used. Used neural network structures in this study were multilayer, probabilistic, and learning vector quantization neural networks. The results of the study were compared with the results of the pervious similar studies reported focusing on chronic obstructive pulmonary and pneumonia diseases diagnosis. The chronic obstructive pulmonary and pneumonia diseases dataset were prepared from a chest diseases hospital's database using patient's epicrisis reports.

journal_name

J Med Syst

authors

Er O,Sertkaya C,Temurtas F,Tanrikulu AC

doi

10.1007/s10916-008-9209-x

subject

Has Abstract

pub_date

2009-12-01 00:00:00

pages

485-92

issue

6

eissn

0148-5598

issn

1573-689X

journal_volume

33

pub_type

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