This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

BackgroundSince most published articles comparing the performance of artificial neural network (ANN) models and logistic regression (LR) models for predicting hepatocellular carcinoma (HCC) outcomes used only a single dataset, the essential issue of internal validity (reproducibility) of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model.Methodology/Principal FindingsPatients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC) curves, Hosmer-Lemeshow (H-L) statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive) parameter affecting in-hospital mortality followed by age and lengths of stay.Conclusions/SignificanceIn comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. 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.

Perioperative anxiety was significantly reduced and overall patient satisfaction increased after viewing a preoperative educational anaesthesia video compared with a standard verbal briefing on anaesthesia.

The purpose of this study was to explore the increasing prevalence of factors affecting hospital charges for primary total hip replacement/total knee replacement (THR/TKR). This study analysed 37,918 THR and 76,727 TKR procedures performed in Taiwan from 1996 to 2004. Odds ratio (OR) and effect size (ES) were calculated to assess the relative change rate. Multiple regression models were employed to predict hospital charges. The following factors were associated with increased hospital charges: age younger than 65 years old; increased disease severity (Charlson comorbidity index [CCI]=1 or ≥2

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The most effective way to reduce the costs of PAC for stroke patients is to minimize the duration of their hospital stay before transfer to rehabilitative PAC. Because it substantially reduces medical costs, rehabilitative PAC should be considered standard care for stroke patients.

Preoperative TACE is not only associated with higher medical utilizations, but it is also correlated with higher mortality rates over a 5-year period. The preoperative TACE does not benefit patients with resectable HCC. The golden standard or clinical guidelines should be developed to provide better clinical decisions and decision support for HCC patients.

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