PSO/ACO algorithm-based risk assessment of human neural tube defects in Heshun County, China / 生物医学与环境科学(英文)
Biomedical and Environmental Sciences
;
(12): 569-576, 2012.
Artigo
em Inglês
| WPRIM
| ID: wpr-320397
ABSTRACT
<p><b>OBJECTIVE</b>To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world.</p><p><b>METHODS</b>The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects (NTDs). A hybrid particle swarm optimization/ant colony optimization (PSO/ACO) algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes.</p><p><b>RESULTS</b>The algorithm was easy to apply, with the accuracy of the results being 69.5%±7.02% at the 95% confidence level.</p><p><b>CONCLUSION</b>The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations.</p>
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Inteligência Artificial
/
China
/
Epidemiologia
/
Fatores de Risco
/
Exposição Ambiental
/
Modelos Biológicos
/
Defeitos do Tubo Neural
Tipo de estudo:
Estudo de etiologia
/
Estudo prognóstico
/
Fatores de risco
Limite:
Humanos
/
Recém-Nascido
País/Região como assunto:
Ásia
Idioma:
Inglês
Revista:
Biomedical and Environmental Sciences
Ano de publicação:
2012
Tipo de documento:
Artigo
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