Title:Lenalidomide in heavily pretreated refractory diffuse large B-cell lymphoma Thank you for the reviewers' comments on our manuscript, now titled " Lenalidomide in Heavily Pretreated Refractory Diffuse Large B-cell Lymphoma: A Case Report. " We are pleased that the reviewers would consider this manuscript for publication in Journal of Medical Case Reports after satisfactory revision. The ma...

Gathering useful insights from social media data has gained great interest over the recent years. User representation can be a key task in mining publicly available user-generated rich content offered by platforms. The way to automatically create meaningful observations about users of network is obtain real-valued vectors for with user embedding learning models. In this study, we presented one ...

Aspect information mining from user comments has become an important means to improve the performance of recommendation systems (RSs). This is because aspect in fine-grained and tends reflect interactions preferences users over items multiple dimensions. These are different ratings, which often explicit linear. Most current RSs based on learn contribution aspects a linear manner, while ignoring...

clinical databases can be categorized as big data, include large quantities of information about patients and their medical conditions. analyzing the quantitative and qualitative clinical data in addition with discovering relationships among huge number of samples using data mining techniques could unveil hidden medical knowledge in terms of correlation and association of apparently independent...

classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. in this article we have presented an appropriate model to classify customers who use internet banking service. the model is deve...

Introduction.............................................................................................................................................................2 � The XTS algorithm itself.........................................................................................................................................2 � Comments From Moses Liskov and Kazuhiko Minematsu.............