nfection prediction after kidney transplantation is significant. Most existing models for predicting transplant infection are statistical, unintelligent, and straightforward. The foremost task of this paper to analyze data, introduce traditional machine learning deep methods from non-temporal temporal scenarios, respectively, comprehensively evaluate the predictive power infection. Specifically...

Background: Blended learning includes an integration of face to face classroom learning with technology enhanced online material. It provides the convenience, speed and cost effectiveness of e-learning with the personal touch of traditional learning. Objective: The objective of the present study was to assess the effectiveness of a combination of e-learning module and traditional teaching (Blen...

Decision analytics commonly focuses on the text mining of financial news sources in order to provide managerial decision support and to predict stock market movements. Existing predictive frameworks almost exclusively apply traditional machine learning methods, whereas recent research indicates that traditional machine learning methods are not sufficiently capable of extracting suitable feature...

Learner autonomy has become the area of interest by many researchers of foreign language learning in the recent years. However, few studies have been done concerning the case of Kurdish learners` autonomy in learning languages. For this reason, the current study addresses this gap. It intends to investigate to what extent Kurdish learners are autonomous in learning English language. The study i...