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Digitising The Campus
Version 1.3 (21/12/12)
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CSE8803 Project: Mortality Prediction in ICU patients
Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.
Constraints for BETYdb
Constraints on the Biofuel Ecophysiological Traits and Yields Database to ensure its logical integrity.
Scott Rohde and David LeBauer
Sum of Squared Errors
A footnote in OpenIntro Statistics, 3rd Edition, Section 5.5.2, Analysis of Variance (ANOVA), relates an identity for the sum of squared errors (SSE).