The purpose of the paper was to apply an Artificial Neural Networks with Radial Basis Function to develop an application model for diagnosing a subclinical ketosis type I and II in dairy cattle. While building the neural network model, applied method...
We present an artificial intelligence (AI)-enhanced monitoring framework designed to assist personnel in evaluating and maintaining animal welfare using a modular architecture. This framework integrates multiple deep learning models to automatically ...
Primary human mast cells (MC) obtained through culturing of blood-derived MC progenitors are the preferred model for the study of MRGPRX2- IgE-mediated MC activation. In order to assess the impact of culture conditions on functional MRGPRX2 express...
Supervised machine-learning (SML) algorithms are potentially powerful tools that may be used for screening cows for infectious diseases such as bovine leukemia virus (BLV) infection. Here, we compared six different SML algorithms to identify the most...
In dairy enterprises, predicting product quality attributes that are influenced by operating parameters is a major task. To reduce quality loss in production, a prediction-based quality control method is proposed in this study. In particular, a seria...
The quality of beef meatballs during repeated freeze-thaw (F-T) cycles was assessed by multiple indicators. This study introduced a novel quality evaluation method using hyperspectral imaging (HSI) and multi-task learning. Seventeen quality indicator...
Milk adulteration poses a global concern, with developing countries facing higher risks due to unsatisfactory monitoring systems and policies. Surprisingly, this common issue has often been overlooked in many countries. Contrary to popular belief, ad...
To quickly achieve nondestructive detection of protein content in fresh milk, this study utilized a network analyzer and an open coaxial probe to analyze the dielectric spectra of milk samples at 100 frequency points within the 2-20 GHz range, focusi...
As a means of preventing mastitis, deep learning for classifying teat-end conditions in dairy cows has not yet been optimized. By using 1426 digital images of dairy cow udders, the extent of teat-end hyperkeratosis was assessed using a four-point sca...
We trained machine learning models to identify IMI in late-lactation cows at dry-off to guide antibiotic treatment, and compared their performance to a rule-based algorithm that is currently used on dairy farms in the United States. We conducted an o...
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