|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|
k nearest neighbours
Feed forward neural network
|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. https://doi.org/10.1016/S0169-4758%2899%2901433-7|
|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.|
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|KayShinn Sommerville1999 Parasitology Today.pdf||Fulltext - Published Version||984.92 kB||Adobe PDF||Under Embargo until 3000-01-01 Request a copy|
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