Artificial Intelligence and Digital Technologies for Cattle Health, Welfare and Precision Management

Cattle health, welfare, and productivity remain central concerns for the livestock sector worldwide, with disease, suboptimal management, and delayed detection contributing substantially to economic loss and compromised animal welfare. Conventional approaches to health monitoring and clinical assessment often rely on manual observation, clinical scoring, and periodic examination, which can be time-consuming, subjective, and limited in detecting early or subclinical changes across large herds. The rapid development of artificial intelligence (AI), digital technologies, and precision livestock farming is transforming cattle health management. Automated sensors, computer vision, wearable devices, imaging, acoustic analysis, biosensors, and machine-learning algorithms are increasingly being integrated into veterinary practice and herd management to support earlier disease detection, objective phenotyping, clinical decision-making, and welfare assessment. Despite this progress, the translation of these technologies into validated, field-ready tools for routine veterinary practice remains uneven, and a consolidated overview of their clinical performance and practical applicability is still lacking.This Research Topic aims to bring together advances in AI, digital technologies, and precision livestock farming that support cattle health, welfare, and clinical management. We welcome original research, reviews, methodological papers, and perspective articles exploring the development, validation, and implementation of innovative technologies for disease detection, health monitoring, decision support, and herd management. Applications may address respiratory, mammary, reproductive, musculoskeletal, metabolic, digestive, and other clinically relevant disorders, as well as population-health surveillance, behavioral monitoring, and welfare assessment. Particular emphasis is placed on methodological rigor, including robust dataset curation, explainable AI, group-aware validation, leakage prevention, external validation, reproducibility, and transparent reporting. Studies comparing novel technologies with established diagnostic methods and demonstrating their feasibility and applicability under field conditions or in routine veterinary practice are particularly encouraged. Beyond presenting new technologies, this Research Topic seeks to identify the opportunities and remaining barriers for translating artificial intelligence and digital innovations into routine cattle veterinary practice. This Research Topic places particular emphasis on methodological rigor, clinical validation, comparison with established diagnostic methods, and real-world implementation to promote technologies that are both scientifically robust and readily applicable in routine cattle veterinary practice.This Research Topic aims to provide a multidisciplinary overview of how AI, digital technologies, and precision livestock farming are transforming cattle health, welfare, and clinical management. By bringing together veterinary clinicians, epidemiologists, animal scientists, engineers, and data scientists, it seeks to promote the development of robust, clinically relevant, and practically applicable technological solutions for cattle production systems. Beyond algorithm development, this Research Topic encourages studies that critically evaluate methodological quality, diagnostic performance, clinical utility, and translational potential. Particular interest is given to research comparing novel technologies with established diagnostic methods and assessing their feasibility, usability, and implementation under field conditions or in routine veterinary practice. Ultimately, the goal is to identify technologies that can improve disease detection, decision-making, herd management, and animal welfare, while highlighting the methodological and practical challenges that must be addressed before widespread adoption. Topic editors: Salvatore Ferraro, Antonio Boccardo, Giuseppe Tardiolo, Francesco Rubino Source: https://www.frontiersin.org/research-topics/85732/artificial-intelligence-and-digital-technologies-for-cattle-health-welfare-and-precision-management