DocumentCode
2860564
Title
Neural network paradigm comparisons for appendicitis diagnoses
Author
Eberhart, R.C. ; Dobbins, R.W. ; Hutton, L.V.
Author_Institution
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
fYear
1991
fDate
12-14 May 1991
Firstpage
298
Lastpage
304
Abstract
The results of comparisons among diagnoses of appendicitis versus nonspecific abdominal pain using three neural-network paradigms are reported. The paradigms used were the back propagation, binary adaptive resonance theory, and fuzzy resonance paradigms. It appears, from the limited testing done, that the back-propagation network performs best. Also discussed is the need to standardize input data files to facilitate paradigm comparisons and minimize software system development time. A structure for network input data files that could contribute to a process of standardization is proposed. The work is part of an effort to develop a medical practice support system to be used in isolated environments such as submarines
Keywords
adaptive systems; medical diagnostic computing; neural nets; abdominal pain; appendicitis diagnoses; back propagation; binary adaptive resonance theory; fuzzy resonance paradigms; input data files; isolated environments; medical practice support system; network input data files; neural-network paradigms; software system development time; Abdomen; Back; Medical diagnostic imaging; Neural networks; Pain; Performance evaluation; Resonance; Software systems; Standardization; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer-Based Medical Systems, 1991. Proceedings of the Fourth Annual IEEE Symposium
Conference_Location
Baltimore, MD
Print_ISBN
0-8186-2164-8
Type
conf
DOI
10.1109/CBMS.1991.128983
Filename
128983
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