Name
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 |
Year | DOI | Venue |
|---|---|---|
1991 | 10.1109/CBMS.1991.128983 | Baltimore, MD |
Keywords | Field | DocType |
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 | Adaptive resonance theory,Data mining,Computer science,Adaptive system,Fuzzy logic,Software system,Artificial intelligence,Artificial neural network,Data file,Backpropagation,Medical diagnosis,Machine learning | Conference |
Citations | PageRank | References |
4 | 2.24 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Russell C. Eberhart | 1 | 18 | 4.73 |
| Roy W. Dobbins | 2 | 16 | 3.94 |
| Larrie V. Hutton | 3 | 4 | 2.24 |