… appraise the performance evaluation of the models and, ideally… DeepSurv is a deep learning
model that uses the log-risk … The Brier score is a measure of the overall performance that …

… for assessing landslide risk, … analysis, during the learning phase, the Tree-based models
(RF and C4.5) outperformed the SVM and NN (DLNN and MLP-NN) models in terms of overall …

… a clinical model to predict the mortality risk of patients with severe COVID-19 infection, based
on demographic, clinical and the first … In this clinical prediction modelling study, we took full …

… Here, we present a mortality risk prediction model for COVID-… by mortality risk, which enables
prediction of physiological … , we integrated the top four best predictive models (LR, SVM, …

… performance of econometric models and machine-learning models in different crash risk
prediction … The selected econometric models include autoregressive integrated moving average …

… machine learning model to discover these patterns directly from the data. Specifically, our
model is provided with full… In conclusion, a deep learning (DL) model that directly leverages full-…

… To assess machine learning (ML) models for predicting … Seven performance measures
were recorded in each … GBT model (cross-validated AUROC, 0.905, overall accuracy on …

… Overall, because of the superior credit scoring prediction capabilities of the LSTM network
… Accuracy is widely employed as a performance evaluation indicator for classification models …

… predicting critical COVID-19 compared to the most efficacious tools available. Hence, artificial
intelligence may be applied for accurate risk prediction … and improved overall management …

… recover and are defined as high-risk patients in this study. These … in the DL model are defined
as layers and are integrated to … Cox proportional hazard model [21] to predict the risk of the …