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The Impact Of Cost On Feature Selection For Classifiers, Richard Clyde Mccrae
The Impact Of Cost On Feature Selection For Classifiers, Richard Clyde Mccrae
CCE Theses and Dissertations
Supervised machine learning models are increasingly being used for medical diagnosis. The diagnostic problem is formulated as a binary classification task in which trained classifiers make predictions based on a set of input features. In diagnosis, these features are typically procedures or tests with associated costs. The cost of applying a trained classifier for diagnosis may be estimated as the total cost of obtaining values for the features that serve as inputs for the classifier. Obtaining classifiers based on a low cost set of input features with acceptable classification accuracy is of interest to practitioners and researchers. What makes this …
Machine Learning Methods For Septic Shock Prediction, Aiman A. Darwiche
Machine Learning Methods For Septic Shock Prediction, Aiman A. Darwiche
CCE Theses and Dissertations
Sepsis is an organ dysfunction life-threatening disease that is caused by a dysregulated body response to infection. Sepsis is difficult to detect at an early stage, and when not detected early, is difficult to treat and results in high mortality rates. Developing improved methods for identifying patients in high risk of suffering septic shock has been the focus of much research in recent years. Building on this body of literature, this dissertation develops an improved method for septic shock prediction. Using the data from the MMIC-III database, an ensemble classifier is trained to identify high-risk patients. A robust prediction model …