Importance weights stability performance (KT-stability) of all the tested Deep Survival NN architectures (blue) and all multivariate CoxPH models fitted. The values in parenthesis for Deep Survival NNs represent the number of input nodes (i.e. the granularity of features’ clusters) and the number of nodes in the last layer before the output. Whereas the parenthesis for CoxPH models report the granularity of the input features’ clusters. Dots represent the average performance value, while bands report the confidence intervals around the mean computed on the K = 10 splits. (PNG)</p
We describe models for survival analysis which are based on a multi-layer perceptron, a type of neur...
(a) Patient stratification defined by hierarchical clustering based on the deep features extracted f...
<p>Comparison of NN model performance (with retrospective validation) vs number of features.</p
Predictive Performance (Harrel CI) of all the tested Deep Survival NN architectures (blue) and all m...
Performance in terms of Kendall-Tau Stability (robustness) and Harrell C-Index (survival prediction ...
<p> and are measures of robustness of a topology to input and parameter perturbations, respectivel...
Comparison of the predicted survival score for the total dataset and each injury mechanism with the ...
Performance comparison of Deep Survival EWAS algorithm with and without pretraining each of the K su...
Access to thesis permanently restricted to Ball State community only.This thesis trains, tests and c...
In medicine, an important objective is predicting patients’ survival based on their molecular and cl...
<p>(A) Overall survival curves of the new predictor (<i>p</i><0.001). (B) Disease free survival curv...
<p>A. Boxplot of the C-IPCW of the 10 TCGA datasets using four prognosis-predicting methods: Cox-nne...
Performance in terms of Kendall-Tau Stability (robustness) and Harrell C-Index (survival prediction ...
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
<p>Performance comparison of ANN, LR and DT models for predicting 1-, 3- and 5-year disease-free sur...
We describe models for survival analysis which are based on a multi-layer perceptron, a type of neur...
(a) Patient stratification defined by hierarchical clustering based on the deep features extracted f...
<p>Comparison of NN model performance (with retrospective validation) vs number of features.</p
Predictive Performance (Harrel CI) of all the tested Deep Survival NN architectures (blue) and all m...
Performance in terms of Kendall-Tau Stability (robustness) and Harrell C-Index (survival prediction ...
<p> and are measures of robustness of a topology to input and parameter perturbations, respectivel...
Comparison of the predicted survival score for the total dataset and each injury mechanism with the ...
Performance comparison of Deep Survival EWAS algorithm with and without pretraining each of the K su...
Access to thesis permanently restricted to Ball State community only.This thesis trains, tests and c...
In medicine, an important objective is predicting patients’ survival based on their molecular and cl...
<p>(A) Overall survival curves of the new predictor (<i>p</i><0.001). (B) Disease free survival curv...
<p>A. Boxplot of the C-IPCW of the 10 TCGA datasets using four prognosis-predicting methods: Cox-nne...
Performance in terms of Kendall-Tau Stability (robustness) and Harrell C-Index (survival prediction ...
Comparison of the average classification accuracy of the networks used in DeephESC and DeephESC 2.0....
<p>Performance comparison of ANN, LR and DT models for predicting 1-, 3- and 5-year disease-free sur...
We describe models for survival analysis which are based on a multi-layer perceptron, a type of neur...
(a) Patient stratification defined by hierarchical clustering based on the deep features extracted f...
<p>Comparison of NN model performance (with retrospective validation) vs number of features.</p