… support vector machine (netSVM), for cancer biomarker … designed for network biomarker
identification by integrating … gene-based methods for network biomarker identification. We then …

… to almost 30% in robustness of the selected biomarkers, along with an improvement of about
15% … support vector machine (netSVM) for identifying biologically network biomarkers using …

… Support vector machines (SVMs) are widely employed in molecular diagnosis of disease …
biomarker discovery algorithm: Gene-Switch-Marker (GSM) to capture meaningful biomarkers …

… cancer is, therefore, vital to its effective and individualized clinical care. The support vector
machine (SVM) is a rising machine … of pathway-based biomarkers as features in the diagnosis …

… The majority of ovarian cancer biomarker discovery efforts focus on the identification of
proteins that can improve the predictive power of presently available diagnostic tests. We here …

… of new cancer biomarkers and are taking our technology for early diagnosis of cancer diseases
to a new … The goal was to identify potential serum biomarkers that influence resistance to …

… Considering that biomarkers are usually only a small fraction of all features, and the total
feature number is not very large in our work, support vector machine combined with partial …

… ‘Support Vectors’ are the data points which lie closest to the optimal hyperplane and lie …
Support Vector Machine), these points are denoted on Figure 2 in boxes. The support vectors are …

… algorithms for gene selection and a fuzzy support vector machine (SVM) as the classifier. …
develop a set of rules for each type of cancer. This improved the abilities of the algorithm by …

… RLNM) status in rectal cancer (RC). Here, we designed support vector machine (SVM) model
… mesenchymal-transition (EMT)-related biomarkers along with clinicopathological variables. …