AIMC Topic: Cattle

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Association of artificial intelligence-predicted milk yield residuals to behavioral patterns and transition success in multiparous dairy cows.

Journal of dairy science
Data-driven health monitoring based on milk yield has shown potential to identify health-perturbing events during the transition period. As a proof of principle, we explored the association between the cow's residual milk yield, that is, the differen...

Artificial intelligence outperforms humans in morphology-based oocyte selection in cattle.

Scientific reports
Evaluating cumulus-oocyte complex (COC) morphology is commonly used to assess oocyte quality. However, clear guidelines on interpreting COC morphology data are lacking as this evaluation method is subjective. In the present study, individual in vitro...

Quantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage.

Scientific reports
In this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parameters to assess the progressive loss of collagen and proteoglycans, mimicking an osteoarthritis condition in ex-vivo bovine cartilage samples. Most ana...

Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis.

Scientific reports
For modeling dairy cattle data, fuzzy logic offers the capability to manage uncertainty, enhance accuracy, facilitate informed decision-making, and optimize resource allocation. A critical aspect of dairy cattle production is the modeling of mastitis...

Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network.

Scientific reports
Cattle health monitoring and management systems are essential for farmers and veterinarians, as traditional manual health checks can be time-consuming and labor-intensive. A critical aspect of such systems is accurate cattle identification, which ena...

Comparison of machine learning and validation methods for high-dimensional accelerometer data to detect foot lesions in dairy cattle.

PloS one
Lameness is one of the major production diseases affecting dairy cattle. It is associated with negative welfare in affected cattle, economic losses at the farm level, and adverse effects on sustainability. Prompt identification of lameness is necessa...

High-Sensitivity Detection of C-Peptide Biomarker for Diabetes by Solid-State Nanopore Using Machine Learning Identification.

The journal of physical chemistry letters
Accurate and early detection of C-peptide, a stable biomarker indicative of diabetes, is crucial for disease diagnosis, treatment, and prevention. This study explores a novel detection methodology using solid-state nanopore technology coupled with ma...

Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis.

Journal of dairy science
Low reticuloruminal pH (rpH) for a prolonged period could lead to SARA. This disease negatively affects cow health and is associated with monetary losses for the dairy industry. The aim of this study was to predict rpH and SARA separately using diffe...

An automatic approach for the classification of lumpy skin disease in cattle.

Tropical animal health and production
Lumpy Skin Disease (LSD) presents significant risks and economic challenges to global cattle farming. Effective and accurate classification of LSD is essential for managing the disease and reducing its impacts. Manual diagnosis is time-consuming, lab...

Machine Learning-Based Analysis of Differentially Expressed Genes in the Muscle Transcriptome Between Beef Cattle and Dairy Cattle.

International journal of molecular sciences
Muscle is a crucial component of cattle, playing a vital role in determining the final quality of beef. This study aimed to identify candidate genes associated with muscle growth and lipid metabolism in beef and dairy cattle by utilizing the public d...