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

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.

[1]  Carlo Zaniolo,et al.  Fast and effective Big Data exploration by clustering , 2020, Future Gener. Comput. Syst..

[2]  Gayo Diallo,et al.  Using Semantic Web Technologies and Multi-agent System for Multi-dimensional Analysis of Open Health Data , 2020, J. Inf. Knowl. Manag..

[3]  Evelyn J. S. Hovenga,et al.  Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics - First Revision , 2011 .

[4]  Oscar Tamburis.  Bridging the Gap between Process Mining and DES Modeling in the Healthcare Domain , 2019, 2019 E-Health and Bioengineering Conference (EHB).

[5]  G. Asokan,et al.  Leveraging “big data” to enhance the effectiveness of “one health” in an era of health informatics , 2015, Journal of epidemiology and global health.

[6]  Hans C. Ossebaard.  One health informatics , 2014, WWW '14 Companion.

[7]  Oscar Tamburis,et al.  Appraising Healthcare Delivery Provision: A Framework to Model Business Processes. , 2017, Studies in health technology and informatics.

[8]  Elio Masciari,et al.  SMART: Stream Monitoring enterprise Activities by RFID Tags , 2012, Inf. Sci..

[9]  Elmer V. Bernstam,et al.  Toward a veterinary informatics research agenda: An analysis of the PubMed-indexed literature , 2007, Int. J. Medical Informatics.

[10]  Fabio Martinelli,et al.  A time series classification approach to game bot detection , 2017, WIMS.

[11]  Henrik Lerner.  Conceptions of Health and Disease in Plants and Animals , 2016 .

[12]  C. Chronaki,et al.  One Digital Health: A Unified Framework for Future Health Ecosystems , 2021, Journal of medical Internet research.

[13]  Kimberly VanderWaal,et al.  Translating Big Data into Smart Data for Veterinary Epidemiology , 2017, Front. Vet. Sci..

[14]  Ali Taghipour,et al.  hs-CRP is strongly associated with coronary heart disease (CHD): A data mining approach using decision tree algorithm , 2017, Comput. Methods Programs Biomed..

[15]  F. Schmitt,et al.  Canine and Feline Spontaneous Mammary Tumours as Models of Human Breast Cancer , 2019 .

[16]  Adequate Mhlanga,et al.  Assessing the Impact of Optimal Health Education Programs on the Control of Zoonotic Diseases , 2020, Comput. Math. Methods Medicine.

[17]  Taranjit Kaur,et al.  SNOMED representation of explanatory knowledge in veterinary clinical pathology. , 2005, Veterinary clinical pathology.

[18]  A. Zaccaroni,et al.  Elements levels in dogs from "triangle of death" and different areas of Campania region (Italy). , 2014, Chemosphere.

[19]  M. Tesic,et al.  Veterinary information management system (VIMS) in the process of notification and management of animal diseases. , 2009 .

[20]  Elio Masciari.  Trajectory Clustering via Effective Partitioning , 2009, FQAS.

[21]  Srebrenko Peši,et al.  Benefits of Using OLAP versus RDBMS for Data Analyses in Health Care Information Systems , .

[22]  A. Mavragani.  Infodemiology and Infoveillance: Scoping Review , 2020, Journal of medical Internet research.

[23]  Jihye Choi,et al.  Web-based infectious disease surveillance systems and public health perspectives: a systematic review , 2016, BMC Public Health.

[24]  Elio Masciari,et al.  A framework for adaptive mail classification , 2002, 14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings..

[25]  J. Mackenzie,et al.  The One Health Approach—Why Is It So Important? , 2019, Tropical medicine and infectious disease.