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Management of filariasis using prediction rules derived from data mining.
- Source :
-
Bioinformation [Bioinformation] 2005 Apr 06; Vol. 1 (1), pp. 8-11. Date of Electronic Publication: 2005 Apr 06. - Publication Year :
- 2005
-
Abstract
- 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.
Details
- Language :
- English
- ISSN :
- 0973-2063
- Volume :
- 1
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Bioinformation
- Publication Type :
- Academic Journal
- Accession number :
- 17597842
- Full Text :
- https://doi.org/10.6026/97320630001008