AIMC Topic: Cattle

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Differentiation of Healthy Ex Vivo Bovine Tissues Using Raman Spectroscopy and Interpretable Machine Learning.

Lasers in surgery and medicine
OBJECTIVES: Integrating machine learning with Raman spectroscopy (RS) shows strong potential for intraoperative guidance in orthopedic procedures, but limited algorithm transparency remains a barrier to clinician trust. This study aims to develop int...

A multi-omics machine learning classifier for outgrowth of cow's milk allergy in children.

Molecular omics
Cow's milk protein allergy (CMA) is one of the most common food allergies in children worldwide. However, it is still not well understood why certain children outgrow their CMA and others do not. While there is increasing evidence for a link of CMA w...

Machine Learning-Driven Multi-Emission Fluorescence Array for Simultaneous Size Discrimination and Quantification of Gold Nanoparticles.

Analytical chemistry
Gold nanoparticles (AuNPs) exhibit size-dependent environmental behaviors and bioaccumulation risks, necessitating precise characterization of their hydrodynamic dimensions and concentrations for toxicity assessment. Existing analytical platforms are...

Modeling enteric methane emission from dairy cows using deep learning approach.

The Science of the total environment
This study explores the application of deep learning (DL) models to predict methane (CH) emissions from enteric fermentation in dairy cows using performance, feeding, behavioral and weather data from automated milking and feeding systems, behavioral ...

Development of prediction equations for immunoglobulin A, immunoglobulin G, and immunoglobulin M concentrations in mature milk from Holstein cows using milk infrared spectral data.

Journal of dairy science
Immunoglobulins in ruminant mammary secretions play a central role in active immune protection of the mammary gland against infections. Ig are present in both colostrum and milk from cows, and interest in routinely quantifying the Ig content in milk ...

Genome Mining and Chemistry-Driven Discovery of a Cell Wall Lipopeptide Signature for subsp. Ancestral Lineage.

ACS infectious diseases
subsp. () causes Johne's disease (JD), a chronic infection responsible for considerable economic losses to dairy industries worldwide. Genetically clonal, has evolved into three distinct genetic lineages designated CII, for bovine strains, and SI ...

Deep learning and genomic best linear unbiased prediction integration: An approach to identify potential nonlinear genetic relationships between traits.

Journal of dairy science
Genomic prediction (GP) aims to predict the breeding values of multiple complex traits, usually assumed to be multivariate normally distributed by the largely used statistical methods, thus imposing linear genetic relationships between traits. Althou...

Machine learning-based detection and quantification of red blood cells in Cholistani cattle: A pilot study.

Research in veterinary science
This study presents the first account of using machine learning to detect and count normal and abnormal red blood cells (RBCs), including tear-drop cells and schistocytes, in Cholistani cattle from Pakistan. A Support Vector Machine (SVM) model was a...

Farmers who implemented this, also implemented that: Use of association-rule-learning to improve biosecurity on dairies.

Preventive veterinary medicine
Biosecurity practices are the cornerstone of disease prevention and control programs. In Canada, their implementation is evaluated with a Risk Assessment Questionnaire (RAQ). Association Rule Learning (ARL) - a non-supervised machine learning algorit...

Artificial neural networks to predict the presence of Neosporosis in cattle.

Mathematical biosciences and engineering : MBE
The prediction of bovine infectious diseases is a constant challenge as generally, only laboratory data is available not allowing the study of their relationship with each disease's risk factors. The diseases neosporosis and bovine viral diarrhea, wh...