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標題Title: Artificial Neural Network Model for Predicting 5-Year Mortality After Surgery for Hepatocellular Carcinoma: A Nationwide Study
作者Authors: 趙頌慈
上傳單位Department: 電機工程系
上傳時間Date: 2015-12-31
上傳者Author: 趙頌慈
審核單位Department: 電機工程系
審核老師Teacher: 趙頌慈
檔案類型Categories: 論文Thesis
關鍵詞Keyword: Hepatocellular carcinoma, Artificial neural network, Logistic regression, Five-year mortality rate
摘要Abstract: Background To validate the use of artificial neural network (ANN) models for predicting 5-year mortality in HCC and to
compare their predictive capability with that of logistic regression (LR) models.
Methods This study retrospectively compared LR and ANN models based on initial clinical data for 22,926 HCC surgery
patients from 1998 to 2009. A global sensitivity analysis was also performed to assess the relative significance of input
parameters in the system model and to rank the importance of variables.
Results Compared to the LR models, the ANN models had a better accuracy rate in 96.57% of cases, a better Hosmer–Lemeshow
statistic in 0.34 of cases, and a better receiver operating characteristic curves in 88.51 % of cases. Surgeon volume was the most
influential (sensitive) parameter affecting 5-year mortality followed by hospital volume and Charlson co-morbidity index.
Conclusions In comparison with the conventional LR model, the ANN model in this study was more accurate in predicting
5-year mortality. Further studies of this model may consider the effect of a more detailed database that includes complications
and clinical examination findings as well as more detailed outcome data.

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