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Applications of Self-Organising Map (SOM) for prioritisation of endemic zones of filariasis in Andhra Pradesh, India.

Identifieur interne : 002585 ( PubMed/Checkpoint ); précédent : 002584; suivant : 002586

Applications of Self-Organising Map (SOM) for prioritisation of endemic zones of filariasis in Andhra Pradesh, India.

Auteurs : Upadhayula Suryanaryana Murty [Inde] ; Mutheneni Srinivasa Rao ; K. Sriram ; K Madhusudhan Rao

Source :

International journal of data mining and bioinformatics [ 1748-5673 ] ; 2011.

RBID : pubmed:21954673

Descripteurs français

KwdFr :
- Algorithmes, Analyse de regroupements, Animaux, Filariose lymphatique (transmission), Filariose lymphatique (épidémiologie), Humains, Inde (épidémiologie), Maladies endémiques, Prévalence.
MESH :
- épidémiologie : Filariose lymphatique, Inde.
- Algorithmes, Analyse de regroupements, Animaux, Humains, Maladies endémiques, Prévalence.
Wicri :
- geographic : Inde.

English descriptors

KwdEn :
- Algorithms, Animals, Cluster Analysis, Elephantiasis, Filarial (epidemiology), Elephantiasis, Filarial (transmission), Endemic Diseases, Humans, India (epidemiology), Prevalence.
MESH :
- geographic , epidemiology : India.
- epidemiology : Elephantiasis, Filarial.
- transmission : Elephantiasis, Filarial.
- Algorithms, Animals, Cluster Analysis, Endemic Diseases, Humans, Prevalence.

Abstract

Entomological and epidemiological data of Lymphatic Filariasis (LF) was collected from 120 villages of four districts of Andhra Pradesh, India. Self-Organising Maps (SOMs), data-mining techniques, was used to classify and prioritise the endemic zones of filariasis. The results show that, SOMs classified all the villages into three major clusters by considering the data of Microfilaria (MF) rate, infection, infectivity rate and Per Man Hour (PMH). By considering the patterns of cluster, appropriate decision can be drawn for each parameter that is responsible for disease transmission of filariasis. Hence, SOM will certainly be a suitable tool for management of filariasis. The detailed application of SOM is discussed in this paper.

PubMed: 21954673

Affiliations:

Inde

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pubmed:21954673

Le document en format XML

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<country xml:lang="fr">Inde</country>
<wicri:regionArea>Bioinformatics Group, Biology Division, Indian Institute of Chemical Technology (CSIR), Tarnaka, Hyderabad 500 007, Andhra Pradesh</wicri:regionArea>
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<front><div type="abstract" xml:lang="en">Entomological and epidemiological data of Lymphatic Filariasis (LF) was collected from 120 villages of four districts of Andhra Pradesh, India. Self-Organising Maps (SOMs), data-mining techniques, was used to classify and prioritise the endemic zones of filariasis. The results show that, SOMs classified all the villages into three major clusters by considering the data of Microfilaria (MF) rate, infection, infectivity rate and Per Man Hour (PMH). By considering the patterns of cluster, appropriate decision can be drawn for each parameter that is responsible for disease transmission of filariasis. Hence, SOM will certainly be a suitable tool for management of filariasis. The detailed application of SOM is discussed in this paper.</div>
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Applications of Self-Organising Map (SOM) for prioritisation of endemic zones of filariasis in Andhra Pradesh, India.

Applications of Self-Organising Map (SOM) for prioritisation of endemic zones of filariasis in Andhra Pradesh, India.

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki