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The use of isovolemic hemodilution to prevent adverse side effects of homologous blood transfusions has increased. The lowest level of hemoglobin that can be tolerated without regional myocardial dysfunction, however, had not been precisely defined for left ventricular myocardium with compromised coronary blood flow. This level was determined in our study(More)
Laboratory safety data are routinely collected in clinical studies for safety monitoring and assessment. We have developed a truncated robust multivariate outlier detection method for identifying subjects with clinically relevant abnormal laboratory measurements. The proposed method can be applied to historical clinical data to establish a multivariate(More)
Biomarker discovery holds the promise for advancing personalized medicine as the biomarkers can help match patients to optimal treatment to improve patient outcomes. However, serious concerns have been raised because very few molecular biomarkers or signatures discovered from high dimensional array data can be successfully validated and applied to clinical(More)
Feature selection is one of the most important research topics in high dimensional array data analysis. We propose a two-way filtering based method that utilizes a pair of statistics coupled with rigorous cross-validation to identify the most informative features from different types of distributions. We evaluate the utility of the proposed adaptive feature(More)
Cross-species research in drug development is novel and challenging. A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments in order to potentially improve the understanding of translation between preclinical and clinical studies(More)
BACKGROUND Potential severe liver injury is identified in clinical trials by ALT >3 × upper limits of normal (ULN) and total bilirubin >2 × ULN, and termed 'Hy's Law' by the US FDA. However, there is limited evidence or validation of these thresholds in clinical trial populations. Using liver chemistry data from clinical trials, decision boundaries were(More)
We developed a novel tool for microarray data analysis that can parsimoniously discover highly predictive genes by finding the optimal trade off between fold change and t-test p value through rigorous cross validation. In addition to find a small set of highly predictive genes, the tool also has a procedure that recursively discovers and removes predictive(More)
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