Monitoring of Respiratory Disease Patterns in a Multimicrobially Infected Pig Population Using Artificial Intelligence and Aggregate Samples.
Animals
Swine
Swine Diseases
/ virology
Artificial Intelligence
Porcine respiratory and reproductive syndrome virus
/ genetics
Porcine Reproductive and Respiratory Syndrome
/ virology
Mycoplasma hyopneumoniae
/ genetics
Coinfection
/ virology
Influenza A virus
/ genetics
Circovirus
/ genetics
Respiratory Tract Infections
/ virology
Orthomyxoviridae Infections
/ virology
Actinobacillus pleuropneumoniae
/ genetics
bioaerosol samples
diagnostics
influenza
novel
oral fluids
respiratory disease
sample types
surveillance
Journal
Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722
Informations de publication
Date de publication:
06 Oct 2024
06 Oct 2024
Historique:
received:
30
08
2024
revised:
02
10
2024
accepted:
04
10
2024
medline:
26
10
2024
pubmed:
26
10
2024
entrez:
26
10
2024
Statut:
epublish
Résumé
A 24/7 AI sound-based coughing monitoring system was applied in combination with oral fluids (OFs) and bioaerosol (AS)-based screening for respiratory pathogens in a conventional pig nursery. The objective was to assess the additional value of the AI to identify disease patterns in association with molecular diagnostics to gain information on the etiology of respiratory distress in a multimicrobially infected pig population. Respiratory distress was measured 24/7 by the AI and compared to human observations. Screening for swine influenza A virus (swIAV), porcine reproductive and respiratory disease virus (PRRSV),
Identifiants
pubmed: 39459909
pii: v16101575
doi: 10.3390/v16101575
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Boehringer Ingelheim Fonds
ID : AO8250107