Rapid identification of female Culexmosquito species using Expert System in the South East Asian region

Rapid identification of mosquito (vector) species is critical for vector control and disease management. Pictorial keys of mosquito species are currently used for the identification of new mosquito species. However, this approach is not very effective. Here, we describe the use of an ID3 algorithm (...

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Autores principales: Murty, Upadhyayula Suryanarayana, Kumar, Duvvuri Venkata Rama Satya, Rao, Mutheneni Srinivasa, Reuben, Rachel, Tewari, Satish Chandra, Hiriyan, J, Akiyama, J, Akavaram, Deepa
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics Publishing Group 2005
Materias:
Web Database
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891630/
https://www.ncbi.nlm.nih.gov/pubmed/17597850
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author Murty, Upadhyayula Suryanarayana
Kumar, Duvvuri Venkata Rama Satya
Rao, Mutheneni Srinivasa
Reuben, Rachel
Tewari, Satish Chandra
Hiriyan, J
Akiyama, J
Akavaram, Deepa
author_facet Murty, Upadhyayula Suryanarayana
Kumar, Duvvuri Venkata Rama Satya
Rao, Mutheneni Srinivasa
Reuben, Rachel
Tewari, Satish Chandra
Hiriyan, J
Akiyama, J
Akavaram, Deepa
author_sort Murty, Upadhyayula Suryanarayana
collection PubMed
description Rapid identification of mosquito (vector) species is critical for vector control and disease management. Pictorial keys of mosquito species are currently used for the identification of new mosquito species. However, this approach is not very effective. Here, we describe the use of an ID3 algorithm (part of artificial intelligence) for the rapid identification of the South East Asian female Culex mosquito species. AVAILABILITY: http://www.envisiict.org/
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spelling pubmed-18916302007-06-27 Rapid identification of female Culexmosquito species using Expert System in the South East Asian region Murty, Upadhyayula Suryanarayana Kumar, Duvvuri Venkata Rama Satya Rao, Mutheneni Srinivasa Reuben, Rachel Tewari, Satish Chandra Hiriyan, J Akiyama, J Akavaram, Deepa Bioinformation Web Database Rapid identification of mosquito (vector) species is critical for vector control and disease management. Pictorial keys of mosquito species are currently used for the identification of new mosquito species. However, this approach is not very effective. Here, we describe the use of an ID3 algorithm (part of artificial intelligence) for the rapid identification of the South East Asian female Culex mosquito species. AVAILABILITY: http://www.envisiict.org/ Biomedical Informatics Publishing Group 2005-08-31 /pmc/articles/PMC1891630/ /pubmed/17597850 Text en © 2005 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Web Database
Murty, Upadhyayula Suryanarayana
Kumar, Duvvuri Venkata Rama Satya
Rao, Mutheneni Srinivasa
Reuben, Rachel
Tewari, Satish Chandra
Hiriyan, J
Akiyama, J
Akavaram, Deepa
Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title_full Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title_fullStr Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title_full_unstemmed Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title_short Rapid identification of female Culexmosquito species using Expert System in the South East Asian region
title_sort rapid identification of female culexmosquito species using expert system in the south east asian region
topic Web Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891630/
https://www.ncbi.nlm.nih.gov/pubmed/17597850
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