A) Compounds tested in the vascular model (n = 111) in order to build the database and depicted as drug class histogram with known cardiovascular (CV) risk highlighted. B) Predictive performance of our classifiers across many adverse events (AUC = 0.5 is the performance of a random classifier). C) The mean receiver operating characteristic (ROC) curve for arteriosclerosis prediction. The distributions represent the performance across a 150 bootstrap cross-validation.</p
<p>ROC curves plotted for the results of leave-one-out cross validation using logistic regression wi...
OBJECTIVE: To compare different prediction models for assessing outcome of patients undergoing non...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
<p>The following table displays the AUC estimates of the 7 independent classifiers trained with two ...
Many risk prediction models have been developed for cardiovascular diseases in different countries d...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
Identification of key factors associated with the risk of developing cardiovascular disease and quan...
<p>The HRV-based classifiers are able to predict vascular events with higher sensitivity and specifi...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
Schematic representing the experimental pipeline of an advanced in vitro human vascular surrogate mo...
Background: Data derived from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) s...
The aim of this article is to review the development and assessment of cardiovascular risk predictio...
Item does not contain fulltextOBJECTIVE: This study was undertaken to assess the predictive ability ...
<p>ROC curves plotted for the results of leave-one-out cross validation using logistic regression wi...
OBJECTIVE: To compare different prediction models for assessing outcome of patients undergoing non...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...
<p>The following table displays the AUC estimates of the 7 independent classifiers trained with two ...
Many risk prediction models have been developed for cardiovascular diseases in different countries d...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
<p>Red, blue, and green curve denotes 5-fold cross-validation prediction performance of Bi-profile B...
Identification of key factors associated with the risk of developing cardiovascular disease and quan...
<p>The HRV-based classifiers are able to predict vascular events with higher sensitivity and specifi...
<p><b>(A)</b> Receiver operating characteristic (ROC) curve. The solid black line indicates the medi...
(A) ROC curves for simulated whole-exome sequencing data, for one cancer type versus all others. Are...
Schematic representing the experimental pipeline of an advanced in vitro human vascular surrogate mo...
Background: Data derived from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) s...
The aim of this article is to review the development and assessment of cardiovascular risk predictio...
Item does not contain fulltextOBJECTIVE: This study was undertaken to assess the predictive ability ...
<p>ROC curves plotted for the results of leave-one-out cross validation using logistic regression wi...
OBJECTIVE: To compare different prediction models for assessing outcome of patients undergoing non...
OBJECTIVES: Receiver operating characteristic (ROC) curves show how well a risk prediction model dis...