Construction of an Artificial Neural Networks Clinical Outcome Prediction Model for Acute Pancreatitis in Emergency Department
| Autor: | Chun-Kai Tseng, 曾俊凱Chun-KaiTseng |
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| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 Emergency department (ED) is a very busy unit in a hospital. The physicians of emergency department must spend their time on new patients’ diagnosis and old patients’ care. Under the limited resources of medical energy, how to identify the critical patients in ED and give aggressive care is an important entity in emergency medicine. In this study, we tried to construct a new prediction model by artificial neural networks (ANN) for the acute pancreatitis with early phase variables, and compared the result with logistic regression (LR) model and modified Glasgow scoring system (mGS). Methods: We reviewed the 45-month patients with the diagnosis of acute pancreatitis in a medical center in Taiwan retrospectively and collected ten occult variables. All of the variables must be available in the four hours after admission. This study chose three different output variables, that were length of hospital stay (LOS) (more than seven days and more than fourteen days) and whether patients expired during admission. Under each output variable, we constructed three predicting models (ANN model、LR model and mGS) to predict the output variable, compared the area under receiver operating characteristic (ROC) curve. Results: In the prediction of whether LOS be more than seven days, the ANN model and LR model all had greater area under the ROC curve (AUC) than mGS (ANN vs. mGS, AUC=0.857:0.787, p |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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