All Outputs (2)

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making (2019)
Journal Article
Romero, M. P., Chang, Y. M., Brunton, L. A., Parry, J., Prosser, A., Upton, P., …Drewe, J. A. (2019). Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making. Preventive Veterinary Medicine, https://doi.org/10.1016/j.prevetmed.2019.104860

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Exploratory machine learning techniques can uncover complex non-linear relationships and interactions wit... Read More about Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Development of Reporting Guidelines for Animal Health Surveillance—AHSURED (2019)
Journal Article
Comin, A., Grewar, J., Schaik, G. V., Schwermer, H., Paré, J., El Allaki, F., …Lindberg, A. (2019). Development of Reporting Guidelines for Animal Health Surveillance—AHSURED. Frontiers in Veterinary Science, 6, https://doi.org/10.3389/fvets.2019.00426

With the current trend in animal health surveillance toward risk-based designs and a gradual transition to output-based standards, greater flexibility in surveillance design is both required and allowed. However, the increase in flexibility requires... Read More about Development of Reporting Guidelines for Animal Health Surveillance—AHSURED.