Towards an automated system for the identification of notifiable pathogens: Using Gyrodactylus salaris as an example

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 s...

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Bibliographic Details
Published in:Parasitology Today
Main Authors: Kay, James W, Shinn, Andrew, Sommerville, Christina
Other Authors: University of Glasgow, Institute of Aquaculture, orcid:0000-0002-5434-2685
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 1999
Subjects:
Parasitology
Pharmacology
Diagnostics
Statistical classifiers
Gyrodactylus
Monogenea
Notifiable pathogen
k nearest neighbours
Feed forward neural network
Kay
Atlantic salmon
Salmo salar
Online Access:http://hdl.handle.net/1893/10104
https://doi.org/10.1016/S0169-4758(99)01433-7
http://dspace.stir.ac.uk/bitstream/1893/10104/1/KayShinn%20%20Sommerville1999%20Parasitology%20Today.pdf
Description
Summary: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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