Review of Modern Diagnostic Methods for the Detection of Bovine Respiratory Diseases

Technological advancements are significantly transforming the diagnosis of respiratory diseases in cattle. Traditional, subjective clinical methods are gradually being replaced by advanced solutions incorporating artificial intelligence, sensor technologies and multidimensional biological data analysis. Modern tools are suitable for continuous, non-invasive health monitoring under real-world production conditions. Integrated systems that combine acoustic, behavioural, imaging and molecular data, supported by predictive algorithms and advanced computational frameworks are becoming increasingly important. Diagnosis is shifting towards a proactive model, focusing on the early detection of deviations from physiological norms, rather than solely responding to clinical signs. This development results in reduced antibiotic use, improved animal welfare and greater economic efficiency. The diagnostic model presented in this study reflects a systemic reorientation of contemporary veterinary medicine towards precise, automated solutions powered by machine learning.