Health information and libraries journal
Jan 1, 2017
BACKGROUND: The knowledge into action model for NHS Scotland provides a framework for librarians and health care staff to support getting evidence into practice. Central to this model is the development of a network of knowledge brokers to facilitate...
BACKGROUND: Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful for event detection and si...
The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the proc...
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects...
Computational intelligence and neuroscience
Nov 2, 2015
Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency ma...
Launched in 2012, Knowledge into Action is the national knowledge management strategy for the health and social care workforce in Scotland. It is transforming the role of the national digital knowledge service--NHS Education for Scotlands' Knowledge ...
SAR and QSAR in environmental research
Sep 21, 2015
Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales t...
Computational intelligence and neuroscience
Sep 14, 2015
Classifying events is challenging in Twitter because tweets texts have a large amount of temporal data with a lot of noise and various kinds of topics. In this paper, we propose a method to classify events from Twitter. We firstly find the distinguis...
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