<p>(A) Discovery and (B) Validation. The bars represent the number of samples with <i>HER2</i> amplification (positive or negative) for each intrinsic subtype based on the patients’ clinical information. The top row is based on the original subtype labels obtained with the PAM50 list and a single classifier (PAM). Middle and bottom rows are based on the labels obtained by Ensemble Learning using the PAM50 and CM1 lists, respectively.</p
<p>(A) Comparison of hierarchical clustering of METABRIC data (left panel) and Perou data (right pan...
<p>This table shows the distribution of the breast cancer patients (Data set 3) in each cluster of r...
Classifiers Performance. The document contains information on the ensemble learning approach with re...
<p>(A) Discovery and (B) Validation. The bars represent the number of samples with ER positive and n...
<p>(A) Discovery and (B) Validation. The bars represent the number of samples with PR positive and n...
<p>The bars represent the number of samples in each breast cancer subtype. In the first row, the lab...
BACKGROUND: Multi-gene lists and single sample predictor models have been currently used to reduce t...
The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to det...
<p>The survival curves for each breast cancer subtype are generated using Cox proportional hazards m...
<div><p>Background</p><p>The prediction of breast cancer intrinsic subtypes has been introduced as a...
<p>Rows contain labels assigned by the majority of classifiers trained with the PAM50 list, while co...
The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to det...
<p>The image shows the similarity between the subtypes distribution for METABRIC discovery (MD) and ...
<p>Rows contain labels assigned by the majority of classifiers trained with the CM1 list, while colu...
Background The prediction of breast cancer intrinsic subtypes has been introduced as a valuable stra...
<p>(A) Comparison of hierarchical clustering of METABRIC data (left panel) and Perou data (right pan...
<p>This table shows the distribution of the breast cancer patients (Data set 3) in each cluster of r...
Classifiers Performance. The document contains information on the ensemble learning approach with re...
<p>(A) Discovery and (B) Validation. The bars represent the number of samples with ER positive and n...
<p>(A) Discovery and (B) Validation. The bars represent the number of samples with PR positive and n...
<p>The bars represent the number of samples in each breast cancer subtype. In the first row, the lab...
BACKGROUND: Multi-gene lists and single sample predictor models have been currently used to reduce t...
The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to det...
<p>The survival curves for each breast cancer subtype are generated using Cox proportional hazards m...
<div><p>Background</p><p>The prediction of breast cancer intrinsic subtypes has been introduced as a...
<p>Rows contain labels assigned by the majority of classifiers trained with the PAM50 list, while co...
The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to det...
<p>The image shows the similarity between the subtypes distribution for METABRIC discovery (MD) and ...
<p>Rows contain labels assigned by the majority of classifiers trained with the CM1 list, while colu...
Background The prediction of breast cancer intrinsic subtypes has been introduced as a valuable stra...
<p>(A) Comparison of hierarchical clustering of METABRIC data (left panel) and Perou data (right pan...
<p>This table shows the distribution of the breast cancer patients (Data set 3) in each cluster of r...
Classifiers Performance. The document contains information on the ensemble learning approach with re...