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Management of filariasis using prediction rules derived from data mining
The present paper demonstrates the application of CART (classification and regression trees) to control a mosquito vector (Culex quinquefasciatus) for bancroftian filariasis in India. The database on filariasis and a commercially available software CART (Salford systems Inc. USA) were used in this s...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics Publishing Group
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891618/ https://www.ncbi.nlm.nih.gov/pubmed/17597842 |
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author | Satya Kumar, Duvvuri Venkata Rama Sriram, Kumarawsamy Rao, Kadiri Madhusudhan Murty, Upadhyayula Suryanarayana |
author_facet | Satya Kumar, Duvvuri Venkata Rama Sriram, Kumarawsamy Rao, Kadiri Madhusudhan Murty, Upadhyayula Suryanarayana |
author_sort | Satya Kumar, Duvvuri Venkata Rama |
collection | PubMed |
description | The present paper demonstrates the application of CART (classification and regression trees) to control a mosquito vector (Culex quinquefasciatus) for bancroftian filariasis in India. The database on filariasis and a commercially available software CART (Salford systems Inc. USA) were used in this study. Baseline entomological data related to bancroftian filariasis was utilized for deriving prediction rules. The data was categorized into three different aspects, namely (1) mosquito abundance, (2) meteorological and (3) socio-economic details. This data was taken from a database developed for a project entitled “Database management system for the control of bancroftian filariasis” sponsored by Ministry of Communication and Information Technology (MC&IT), Government of India, New Delhi. Predictor variables (maximum temperature, minimum temperature, rain fall, relative humidity, wind speed, house type) were ranked by CART according to their influence on the target variable (month). The approach is useful for forecasting vector (mosquito) densities in forthcoming seasons. |
format | Text |
id | pubmed-1891618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-18916182007-06-27 Management of filariasis using prediction rules derived from data mining Satya Kumar, Duvvuri Venkata Rama Sriram, Kumarawsamy Rao, Kadiri Madhusudhan Murty, Upadhyayula Suryanarayana Bioinformation Disease Management Model The present paper demonstrates the application of CART (classification and regression trees) to control a mosquito vector (Culex quinquefasciatus) for bancroftian filariasis in India. The database on filariasis and a commercially available software CART (Salford systems Inc. USA) were used in this study. Baseline entomological data related to bancroftian filariasis was utilized for deriving prediction rules. The data was categorized into three different aspects, namely (1) mosquito abundance, (2) meteorological and (3) socio-economic details. This data was taken from a database developed for a project entitled “Database management system for the control of bancroftian filariasis” sponsored by Ministry of Communication and Information Technology (MC&IT), Government of India, New Delhi. Predictor variables (maximum temperature, minimum temperature, rain fall, relative humidity, wind speed, house type) were ranked by CART according to their influence on the target variable (month). The approach is useful for forecasting vector (mosquito) densities in forthcoming seasons. Biomedical Informatics Publishing Group 2005-04-06 /pmc/articles/PMC1891618/ /pubmed/17597842 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 | Disease Management Model Satya Kumar, Duvvuri Venkata Rama Sriram, Kumarawsamy Rao, Kadiri Madhusudhan Murty, Upadhyayula Suryanarayana Management of filariasis using prediction rules derived from data mining |
title | Management of filariasis using prediction rules derived from data mining |
title_full | Management of filariasis using prediction rules derived from data mining |
title_fullStr | Management of filariasis using prediction rules derived from data mining |
title_full_unstemmed | Management of filariasis using prediction rules derived from data mining |
title_short | Management of filariasis using prediction rules derived from data mining |
title_sort | management of filariasis using prediction rules derived from data mining |
topic | Disease Management Model |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891618/ https://www.ncbi.nlm.nih.gov/pubmed/17597842 |
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