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Appears in Collections:Aquaculture Journal Articles
Peer Review Status: Refereed
Title: Towards an automated system for the identification of notifiable pathogens: Using Gyrodactylus salaris as an example
Author(s): Kay, James W
Shinn, Andrew
Sommerville, Christina
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Keywords: Parasitology
Statistical classifiers
Notifiable pathogen
k nearest neighbours
Feed forward neural network
Issue Date: May-1999
Date Deposited: 23-Nov-2012
Citation: Kay JW, Shinn A & Sommerville C (1999) Towards an automated system for the identification of notifiable pathogens: Using Gyrodactylus salaris as an example. Parasitology Today, 15 (5), pp. 201-206.
Abstract: Simple and rapid identification of pathogen species is crucial to the control of many diseases. Here, James Kay, Andrew Shinn and Christina Sommerville demonstrate that statistical classifiers discriminate a notifiable pathogen Gyrodactylus salaris Malmberg, 1957, a lethal ectoparasite of Atlantic salmon, Salmo salar L., from its benign close relatives.
DOI Link: 10.1016/S0169-4758(99)01433-7
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