Automated Detection of Chagas Vector Using Artificial Intelligence (#950)
Read ArticleDate of Conference
July 17-19, 2024
Published In
"Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0."
Location of Conference
Costa Rica
Authors
Ludeña, Victoria
Pinzon, Cristian
Bajo, Javier
Serrano, Emilio
Abstract
This scientific article proposes the application of artificial intelligence as an innovative strategy to improve the detection of Trypanosoma Cruzi carriers in Panama. An analysis of various methods and algorithms previously used in pathogen detection, including multilayer architectures, Resnet34 and MALDI-TOF, is performed, with a particular focus on the Rhodnius and Triatoma families, which are the main vectors of this disease in the region. Through a local search and literature review, together with the collection of relevant data, a model was designed using artificial intelligence algorithms. This model has as its main objective the identification of vectors through images, offering an assistance tool for specialists in the field. The project culminates with the development of a free software application for specialists, capable of differentiating between two species of triatomines, thus providing an innovative resource for the fight against Chagas disease.