Applying a model for rectal cancer would require microarray and/or proteomics data, gathered at one or two time points during therapy.
In the first case on rectal cancer, tumor regression grade, lymph node status, and circumferential margin involvement (CRM) are predicted for 36 patients based on microarray and proteomics data, gathered at two time points during therapy.
For the rectal cancer outcomes, the highest leave-one-out (LOO) areas under the receiver operating characteristic curves (AUC) were obtained when combining microarray and proteomics data gathered during therapy and ranged from 0.927 to 0.987.
For the data on rectal cancer, all three outcomes - a tumor regression grading system and two prognostic factors - could be predicted most accurately and most cost-efficiently with an AUC ranging from 0.9269 to 0.9870 when fusing microarray and proteomics data gathered during therapy (MPT1; Table 2).
Hence, we can safely conclude that MMP-9 protein expression in vivo strongly supports both in silico analyses on microarray dataset as well as data gathered from analysis of breast cancer cell lines.> -wrap-foot> OR = odds ratio, CI = confidence interval.
Big Volume comes from large amounts of records stored for patients: for example, in some datasets each instance is quite large (e.g. datasets using MRI images or gene microarrays for each patient), while others have a large pool with which to gather data (such as social media data gathered from a population).
We analyzed the data gathered from autumn 2010 to autumn 2011.
Therefore, we carried out a new study to estimate the performance of models based on independently gathered microarray data in an unbiased way.
In this study we describe the results of the evaluation of models developed based on the data from our previously published pilot study [ 2] using PCA analysis or LS-SVMs on independently gathered microarray data.
At the same time, it is becoming important to use more than a single data set when analyzing microarray data [6] and gather hundreds or thousands of samples to develop prognostic markers [7].
