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Salud, Ciencia y Tecnología Metaverse Basic and Applied Research Data & Metadata Interdisciplinary Rehabilitation Salud, Ciencia y Tecnología - Serie de Conferencias Community and Interculturality in Dialogue Seminars in Medical Writing and Education Health Leadership and Quality of Life Gamification and Augmented Reality Southern perspective / Perspectiva austral
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Original
Published: 2023-12-29
DOI: https://doi.org/10.56294/dm2023114

An artificial intelligence-based approach for an urgent detection of the pesticide responsible of intoxication

By
Rajae Ghanimi ,
Rajae Ghanimi

Ibn Tofail University

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Fadoua Ghanimi ,
Fadoua Ghanimi

Ibn Tofail University, Av. de L'Université, Kénitra-Morocco

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Ilyas Ghanimi ,
Ilyas Ghanimi

Ibn Tofail University, Av. de L'Université, Kénitra-Morocco

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Abdelmajid Soulaymani ,
Abdelmajid Soulaymani

Ibn Tofail University, Av. de L'Université, Kénitra-Morocco

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Abstract

Acute poisoning by pesticides in Morocco is an important public health issue, because the use of pesticides has become both massive and anarchic. This is the cause of deaths whose incidence is unfortunately increasing. Unfortunately, these deaths are not always accidental. Pesticides are also used as a means of suicide; according to the WHO, these are means suicide chemicals most used in the world, since, out of the 800,000 suicides recorded per year, more than a third are caused by this type of product. Even more serious, these suicides are currently being observed among children and teenagers. Faced with this alarming figure, and in order to prevent deaths and improve emergency treatment of cases of pesticide poisoning, it becomes important to use the potential of artificial intelligence in the treatment of these admissions. Our approach is essentially based on machine learning algorithms, including decision support software capable of predicting, based on major clinical signs, the most likely pesticide responsible of the intoxication in the triage room. This, before moving on to the confirmation stage based on biological and toxicological investigations, which are often costly and time-consuming.

Keywords:

Pesticide,
Machine Learning,
Artificial Intelligence,
Diagnostics,
Emergencies,
Triage Room,

How to Cite

1.
Ghanimi R, Ghanimi F, Ghanimi I, Soulaymani A. An artificial intelligence-based approach for an urgent detection of the pesticide responsible of intoxication. Data and Metadata [Internet]. 2023 Dec. 29 [cited 2024 Jul. 27];2:114. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/114

Copyright Notice

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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Vol. 2 (2023)
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