Prospects for predictive modeling of transition cow diseases.
Anim Health Res Rev
; 20(1): 19-30, 2019 06.
Article
em En
| MEDLINE
| ID: mdl-31895019
ABSTRACT
Transition cow diseases can negatively impact animal welfare and reduce dairy herd profitability. Transition cow disease incidence has remained relatively stable over time despite monitoring and management efforts aimed to reduce the risk of developing diseases. Dairy cattle disease risk is monitored by assessing multiple factors, including certain biomarker test results, health records, feed intake, body condition score, and milk production. However, these factors, which are used to make herd management decisions, are often reviewed separately without considering the correlation between them. In addition, the biomarkers that are currently used for monitoring may not be representative of the complex physiological changes that occur during the transition period. Predictive modeling, which uses data to predict future or current outcomes, is a method that can be used to combine the most predictive variables and their interactions efficiently. The use of an effective predictive model with relevant predictors for transition cow diseases will result in better targeted interventions, and therefore lower disease incidence. This review will discuss predictive modeling methods and candidate variables in the context of transition cow diseases. The next step is to investigate novel biomarkers and statistical methods that are best suited for the prediction of transition cow diseases.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Doenças dos Bovinos
/
Modelos Biológicos
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Revista:
Anim Health Res Rev
Ano de publicação:
2019
Tipo de documento:
Article