Mobile app for targeted selective treatment of haemonchosis in sheep.

Autor: de Souza LF; Digital Signal Processing Laboratory, Universidade Federal de Santa Catarina, Florianópolis, SC 88040-900, Brazil., Costa MH; Department of Electrical and Electronic Engineering, Universidade Federal de Santa Catarina, Florianópolis, SC 88040-900, Brazil. Electronic address: costa@eel.ufsc.br., Riet-Correa B; Faculty of Veterinary, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS 90540-000, Brazil.
Jazyk: angličtina
Zdroj: Veterinary parasitology [Vet Parasitol] 2023 Apr; Vol. 316, pp. 109902. Date of Electronic Publication: 2023 Feb 28.
DOI: 10.1016/j.vetpar.2023.109902
Abstrakt: Livestock is an important part of many countries gross domestic product, and sanitary control impacts herd management costs. To contribute to incorporating new technologies into this economic chain, this work presents a mobile application for decision assistance to treatment against parasitic infection by Haemonchus contortus in small ruminants. Based on the Android system, the proposed software is a semi-automated computer-aided procedure to assist Famacha© pre-trained farmers in applying anthelmintic treatment. It mimics the two-class decision procedure performed by the veterinarian with the help of the Famacha© card. The embedded cell phone camera was employed to acquire an image from the ocular conjunctival mucosa, classifying the animal as healthy or anemic. Two machine-learning strategies were assessed, resulting in an accuracy of 83 % for a neural network and 87 % for a support vector machine (SVM). The SVM classifier was embedded into the app and made available for evaluation. This work is particularly interesting to small property owners from regions with difficult access or restrictions on obtaining continuous post-training technical guidance to use the Famacha© method effectively.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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