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
Link To Document :
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