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Sus scrofa

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Machine learning for intraoperative prediction of viability in ischemic small intestine.

Physiological measurement
OBJECTIVE: Evaluation of intestinal viability is essential in surgical decision-making in patients with acute intestinal ischemia. There has been no substantial change in the mortality rate (30%-93%) of patients with acute mesenteric ischemia (AMI) s...

Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.

Genomics
Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miR...

Scoring pleurisy in slaughtered pigs using convolutional neural networks.

Veterinary research
Diseases of the respiratory system are known to negatively impact the profitability of the pig industry, worldwide. Considering the relatively short lifespan of pigs, lesions can be still evident at slaughter, where they can be usefully recorded and ...

SilencerDB: a comprehensive database of silencers.

Nucleic acids research
Gene regulatory elements, including promoters, enhancers, silencers, etc., control transcriptional programs in a spatiotemporal manner. Though these elements are known to be able to induce either positive or negative transcriptional control, the comm...

Endoscopy-assisted magnetic navigation of biohybrid soft microrobots with rapid endoluminal delivery and imaging.

Science robotics
High-precision delivery of microrobots at the whole-body scale is of considerable importance for efforts toward targeted therapeutic intervention. However, vision-based control of microrobots, to deep and narrow spaces inside the body, remains a chal...

A computer vision image differential approach for automatic detection of aggressive behavior in pigs using deep learning.

Journal of animal science
Pig aggression is a major problem facing the industry as it negatively affects both the welfare and the productivity of group-housed pigs. This study aimed to use a supervised deep learning (DL) approach based on a convolutional neural network (CNN) ...

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 ...

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...

Estimating body weight in Sujiang pigs using artificial neural network, nearest neighbor, and CART algorithms: a comparative study using morphological measurements.

Tropical animal health and production
The objectives of this study were to evaluate different machine learning algorithms for predicting body weight (BW) in Sujiang pigs using the following morphological traits: age, body length (BL), backfat thickness (BFT), chest circumference (CC), bo...