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Modeling Of Covid-19 Clinical Outcomes In Mexico: An Analysis Of Demographic, Clinical, And Chronic Disease Factors, Livia Clarete
Modeling Of Covid-19 Clinical Outcomes In Mexico: An Analysis Of Demographic, Clinical, And Chronic Disease Factors, Livia Clarete
Dissertations, Theses, and Capstone Projects
This study explores COVID-19 clinical outcomes in Mexico, focusing on demographic, clinical, and chronic disease variables to develop predictive models. In the binary classification task, the Ada Boost Classifier distinguishes survivors from non-survivors, with age, sex, ethnicity, and chronic medical conditions influencing outcomes. In multiclass classification, the Gradient Boosting Classifier categorizes patients into outcome groups.
Demographic variables, especially age, are crucial for predicting COVID-19 outcomes for both the binary and multiclass classification tasks. Clinical information about previous conditions, including chronic diseases, also holds relevance, especially diabetes, immunocompromise, and cardiovascular diseases. These insights inform public health measures and healthcare strategies, emphasizing …