Title

Forecasting Pain and Discomfort for Canines with Disease for Establishing Appropriate Medication Levels

Document Type

Book Chapter

Publication/Presentation Date

2016

Publisher

Emerald Group Publishing Limited

Abstract/Description

Abstract. This is the third in a series of papers aimed at providing models effective in predicting the degree of pain and discomfort in canines. The first two papers provided benchmarking and examination of dogs suffering from osteoarthritis (OA). In this chapter, we extend the study to include dogs suffering from OA, sarcoma, and oral mucositis (a side effect of chemotherapy and radiation treatments). The R programming language and SAS JMP are used to clean data, generate ANOVA, LSR regression, decision tree, and nominal logistic regression models to predict changes in activity levels associated with the progression of arthritis. The predictive models provide a diagnostic basis for determining the degree of disease in a dog (based on demographics and activity levels) and provide forecasts that assist in establishing appropriate medication dosages for suffering dogs.

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