Utilize este identificador para referenciar este registo: http://hdl.handle.net/10174/19180

Título: An Assessment to Toxicological Risk of Pesticide Exposure
Autor(es): Coelho, Cristina
Martins, M. Rosário
Lima, Nelson
Vicente, Henrique
Neves, José
Editor(es): Li, Hongxiu
Nykänen, Pirkko
Suomi, Reima
Wickramasinghe, Nilmini
Widén, Gunilla
Zhan, Ming
Palavras Chave: Pesticide Exposure
Toxicity
Environmental Fate
Artificial Intelligence
Logic Programming
Knowledge Representation and Reasoning
Artificial Neuronal Networks
Incomplete Information
Data: 2016
Editora: Springer International Publishing
Citação: Coelho, C., Martins, M.R., Lima, N., Vicente, H. & Neves, J., An Assessment to Toxicological Risk of Pesticide Exposure. In H. Li, P. Nykänen, R. Suomi, N. Wickramasinghe, G. Widén & M. Zhan, Eds., Building Sustainable Health Eco-systems, Communications in Computer and Information Science, Vol. 636, pp. 139-150. Springer International Publishing, Cham, Switzerland, 2016.
Resumo: On the one hand, pesticides may be absorbed into the body orally, dermally, ocularly and by inhalation and the human exposure may be dietary, recreational and/or occupational where toxicity could be acute or chronic. On the other hand, the environmental fate and toxicity of the pesticide is contingent on the physico-chemical characteristics of pesticide, the soil composition and adsorption. Human toxicity is also dependent on the exposure time and individual’s susceptibility. Therefore, this work will focus on the development of an Artificial Intelligence based diagnosis support system to assess the pesticide toxicological risk to humanoid, built under a formal framework based on Logic Programming to knowledge representation and reasoning, complemented with an approach to computing grounded on Artificial Neural Networks. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting.
URI: http://link.springer.com/chapter/10.1007/978-3-319-44672-1_12
http://hdl.handle.net/10174/19180
ISBN: 978-3-319-44671-4
ISSN: 1865-0929
Tipo: bookPart
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