Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10-Year Retrospective Study
The RF model shows promise for predicting BLV seropositivity in beef cattle. Key predictive risk factors include the dry season months coinciding with pre-calving and calving seasons and geographic location. These findings could help develop predictive tools for effective screening for BLV infection and targeted interventions.
Authors
- Michael Short (ORCID: https://orcid.org/0000-0001-6290-4396)
- Yugendar R. Bommineni
- J.H.J. Bittar (ORCID: https://orcid.org/0000-0002-6440-6785)
- Ameer Megahed (ORCID: https://orcid.org/0000-0003-2006-8873)
Institutions
- Florida Department of Agriculture and Consumer Services (US)
- Benha University (EG)
- University of Florida (US)
- Florida College (US)
Publication Details
- Journal
- Journal of Veterinary Internal Medicine
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1111/jvim.70070
- Primary Topic
- T-cell and Retrovirus Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00