Skip to main navigation menu Skip to main content Skip to site footer
×
Español (España) | English
Editorial
Home
Indexing
Original

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

By
Rajae Ghanimi ,
Rajae Ghanimi

Ibn Tofail University

Search this author on:

PubMed | Google Scholar
Fadoua Ghanimi ,
Fadoua Ghanimi

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

Search this author on:

PubMed | Google Scholar
Ilyas Ghanimi ,
Ilyas Ghanimi

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

Search this author on:

PubMed | Google Scholar
Abdelmajid Soulaymani ,
Abdelmajid Soulaymani

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

Search this author on:

PubMed | Google Scholar

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.

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 Apr. 22];2:114. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/114

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

Article metrics

Google scholar: See link

Metrics

Metrics Loading ...

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.