AIMC Topic: Swine

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Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data.

The Journal of infection
OBJECTIVES: Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in...

Development of a pig wean-quality score using machine-learning algorithms to characterize and classify groups with high mortality risk under field conditions.

Preventive veterinary medicine
Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of ...

Imitating the respiratory activity of the brain stem by using artificial neural networks: exploratory study on an animal model of lactic acidosis and proof of concept.

Journal of clinical monitoring and computing
Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute volume during spontaneous breathing after being trained using data from an animal model of...

Characterizing feral swine movement across the contiguous United States using neural networks and genetic data.

Molecular ecology
Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine (Sus scrofa × domesticus) are recognized as being a...

A Fluorescent Immunochromatography Test Strip for the Rapid Identification of SVV and FMDV.

Transboundary and emerging diseases
Seneca Valley virus (SVV) and foot-and-mouth disease virus (FMDV) belong to the Picornaviridae family, which can cause similar symptoms. After infection, pigs will develop fever; loss of appetite; blister lesions on the skin and mucous membrane of th...

Investigation of heat-induced pork batter quality detection and change mechanisms using Raman spectroscopy coupled with deep learning algorithms.

Food chemistry
Pork batter quality significantly affects its product. Herein, this study explored the use of Raman spectroscopy combined with deep learning algorithms for rapidly detecting pork batter quality and revealing the mechanisms of quality changes during h...

Development of artificial intelligence-driven biosignal-sensitive cardiopulmonary resuscitation robot.

Resuscitation
AIM OF THE STUDY: We evaluated whether an artificial intelligence (AI)-driven robot cardiopulmonary resuscitation (CPR) could improve hemodynamic parameters and clinical outcomes.

Virtual-screening of xanthine oxidase inhibitory peptides: Inhibition mechanisms and prediction of activity using machine-learning.

Food chemistry
Xanthine oxidase (XO) inhibitory peptides can prevent XO-mediated hyperuricemia. Currently, QSAR about XO inhibitory peptides with different lengths remains to be enriched. Here, XO inhibitory peptides were obtained from porcine visceral proteins thr...

Ultrasound Image Temperature Monitoring Based on a Temporal-Informed Neural Network.

Sensors (Basel, Switzerland)
Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical challenge for ensuring treatment efficacy and patient safety. This study presents a novel approach to simulate real MH and precisely determine the tem...

A proposal for cut marks classification using machine learning: Serrated vs. non-serrated, single vs. double-beveled knives.

Journal of forensic sciences
In tool mark identification, there is still a lack of characteristics and methodologies standardization used to analyze and describe sharp force trauma marks on skeletal remains. This study presents a classification method for cut marks on human bone...