This project explores the application of Generalized Linear Models (GLMs) to mortality data, focusing on predicting the likelihood of death among hepatitis patients. Using logistic regression, the study identifies key risk factors influencing patient survival, including demographic and clinical variables.
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This project explores the application of Generalized Linear Models (GLMs) to mortality data, focusing on predicting the likelihood of death among hepatitis patients. Using logistic regression, the study identifies key risk factors influencing patient survival, including demographic and clinical variables.
KwesiAppau/GLM-Applications-to-Mortality-Data
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This project explores the application of Generalized Linear Models (GLMs) to mortality data, focusing on predicting the likelihood of death among hepatitis patients. Using logistic regression, the study identifies key risk factors influencing patient survival, including demographic and clinical variables.
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