Exploratory analysis of methods for automated classification of clinical diagnoses in Veterinary Medicine

Abstract

The present work describes the analysis conducted on the diagnoses made during the general physical examinations in the decade 2010–2020, starting from the DB of the EMR previously implemented in the University Veterinary Teaching Hospital at Federico II University of Naples. A decision tree algorithm was implemented to work out a predictive model for an effective recognition of neoplastic diseases and zoonoses for cats and dogs from Campania Region. The results achievable by data mining techniques for what concerns computer aided disease diagnosis and exploration of risk factors and their relations to diseases, show the increasing importance of Veterinary Informatics within the wider field of Biomedical and Health Informatics, and in particular its capacity to point out the existing connections between humans, animals, and surrounding environment, according to the One (Digital) Health perspective specifics.