Forecasting Pain and Discomfort for Canines with Disease for Establishing Appropriate Medication Levels
Emerald Group Publishing Limited
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.
Miori, Virginia M., Zhenpeng Miao, and Yingdao Qu. "Forecasting Pain and Discomfort for Canines with Disease for Establishing Appropriate Medication Levels." Advances in Business and Management Forecasting, Volume 11. Emerald Group Publishing Limited, 2016. 51-99.
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