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Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
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- Algorithms (1)
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- Cholera transmission (1)
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- Computer aided diagnosis (1)
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- Computer-aided detection (1)
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- Thomas F. and Kate Miller Jeffress Memorial Trust (1)
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
2004 Jeffress Research Grant Awards
2004 Jeffress Research Grant Awards
Virginia Journal of Science
List of winners of the 2004 Jeffress Research Grant Awards.
Characterization Of Β-Lactam Resistant Pandemic Serotypes Of Vibrio Cholerae Isolated From Ships' Ballast Tanks And Coastal Waters, Amanda Lynn Goodrich
Characterization Of Β-Lactam Resistant Pandemic Serotypes Of Vibrio Cholerae Isolated From Ships' Ballast Tanks And Coastal Waters, Amanda Lynn Goodrich
OES Theses and Dissertations
Vibrio cholerae serotypes 01 and 0139 are responsible for world-wide epidemics of cholera. These pandemic causing strains must possess genes that encode for the cholera toxin (CTX) and toxin co-regulated pili (TCP) in order to infect their hosts. In this study, 284 isolates of Vibrio cholerae from ballast and coastal waters were serotyped, with 11 % testing positive for serotype 01 and 21 % testing positive for serotype 0139. PCR assays were used to detect the presence of ctxA and tcpA genes in all positive isolates, none of which contained ctxA while 2% of the isolates contained tcpA. The 01 …
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Electrical & Computer Engineering Faculty Publications
We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …