Development and validation of a machine learning model for clinical wellness visit classification in cats and dogs
The model exhibits high specificity and sensitivity, ensuring accurate identification of a high proportion of wellness visits. Overall, this model holds promise for advancing research on preventive care's role in subclinical disease identification, but prospective studies are needed for validation.
Authors
- Julia Riggott
- Donald Szlosek (ORCID: https://orcid.org/0000-0001-8096-7366)
- Dave Kincaid
- Michael J. Coyne (ORCID: https://orcid.org/0000-0003-4107-2353)
- Kevin K. Knight (ORCID: https://orcid.org/0000-0001-9117-1718)
- Donald J. McCrann
Institutions
- IDEXX Laboratories (United States) (US)
Publication Details
- Journal
- Frontiers in Veterinary Science
- Published
- 2024-08-30
- DOI
- https://doi.org/10.3389/fvets.2024.1348162
- Citations
- 5
- Primary Topic
- Human-Animal Interaction Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.75