AI Medical Compendium Journal:
Research in veterinary science

Showing 1 to 10 of 15 articles

Cardiac biomarkers N-terminal fragment of the prohormone B-type natriuretic peptide and cardiac troponin I for characterization of the cardiac disease phenotype of the English Bull Terrier.

Research in veterinary science
The N-terminal fragment of prohormone B-type natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI) contribute information regarding cardiac load and function and myocardial injury, respectively, to the clinical work-up of dogs with heart dise...

Predictive modeling based on machine learning for mapping risk areas of human sporotrichosis in southeastern Brazil.

Research in veterinary science
Sporotrichosis, a zoonotic mycosis with a growing public health impact, requires innovative methods to map risk areas. This study applied machine learning techniques, Artificial Neural Networks (ANN), and Decision Trees (DT) to integrate sociodemogra...

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...

Unveiling livestock trade trends: A beginner's guide to generative AI-powered visualization.

Research in veterinary science
This tutorial, rooted in the context of livestock research, is designed to assist novice or non-programmers in visualizing trends in livestock exports between the US and Japan using Python and generative AI systems such as Microsoft's Copilot and Goo...

Deep-learning classification of teat-end conditions in Holstein cattle.

Research in veterinary science
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...

Development of an artificial intelligence-based algorithm for predicting the severity of myxomatous mitral valve disease from thoracic radiographs by using two grading systems.

Research in veterinary science
A heart-convolutional neural network (heart-CNN) was designed and tested for the automatic classification of chest radiographs in dogs affected by myxomatous mitral valve disease (MMVD) at different stages of disease severity. A retrospective and mul...

Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations.

Research in veterinary science
The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This manuscript provides an overview of the current state and future prospects of AI in veterinary diagnos...

The determination of mastitis severity at 4-level using Milk physical properties: A deep learning approach via MLP and evaluation at different SCC thresholds.

Research in veterinary science
Current research aims to generate an alternative model to classical methods in the determination of subclinical mastitis at 4 levels (healthy, suspicious, subclinical, and clinical). For this purpose, multilayer perceptron (MLP) artificial neural net...

The groundbreaking impact of digitalization and artificial intelligence in sheep farming.

Research in veterinary science
The integration of digitalization and Artificial Intelligence (AI) has marked the onset of a new era of efficient sheep farming in multiple aspects ranging from the general well-being of sheep to advanced web-based management applications. The result...

Utilization of sentiment analysis to assess and compare negative finding reporting in veterinary and human literature.

Research in veterinary science
Publication bias and the decreased publication of trials with negative or non-significant results is a well-recognized problem in human and veterinary medical publications. These biases may present an incomplete picture of evidence-based clinical car...