We determined whether total hip arthroplasty (THA) patients could test their own prothrombin time reliably over 6 weeks of anticoagulation prophylaxis with a portable device that measures prothrombin time and whether self-testing would improve or maintain the quality of care at a lower cost than our standard procedure. Forty-six THA patients participated in the study and were compared with a ma...

Classification is a fundamental problem in machine learning and data mining. During the past decades, numerous classification methods have been presented based on different principles. However, most existing classifiers cast as an optimization do not address issue of statistical significance. In this paper, we formulate binary two-sample testing problem. More precisely, our model generic framew...

So far, model-based testing approaches have mostly been used in testing through various kinds of APIs. In practice, however, testing through a GUI is another equally important application area, which introduces new challenges. In this paper, we introduce a new methodology for model-based GUI testing. This includes using Labeled Transition Systems (LTSs) in conjunction with action word and keywo...

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. However, adhering to the regular statistical assumptions regarding the null distributions of test statistics in such large-scale multiple testing frameworks has the potential of leading to incorrect significance testing results and biased inference. Thi...