IN HER NEWS FOCUS STORY “CHINA’S PUBLICAtion bazaar” (29 November 2013, p. 1035), M. Hvistendahl points out that many scientists and organizations are starting to abandon the use of impact factors to evaluate a single researcher. Science leaders in China are considering new standards as well, such as total paper citations. The use of the Science Citation Index (SCI) may have some disadvantages,...

BACKGROUND Clinical preventive services improve patient health, and reminder systems can increase the use of such services. However, physician organizations often underutilize clinical preventive service reminders. Little is known about the incentives, capabilities, and organizational characteristics associated with the use of reminders by physician organizations. METHODS The predictors of pa...

In response to a new Federal initiative to improve the U.S. long-term services and supports (LTSS) system, this commentary discusses an array of policies and practices that could potentially improve LTSS provision by shifting from institutional to community-based services, increasing equity across populations, offering consumers more choice and control, improving conditions for workers and care...

Interactive Causation Agent (ICA), a novel unsupervised adaptive neurosymbolic model based on a theory of causality (Interactive Causation), is defined, offering an interactive computational approach to problems in the algorithmic computing of interaction. Interactive Causation provides a compatible framework of nonalgorithmic computation and environment, permitting tractable computation of tem...

Biological systems (e.g., rats) have efficient and robust localization abilities provided by the so called, place cells, which are found in the hippocampus of rodents and primates (these cells encode locations of the animal’s environment). This work seeks to model these place cells by employing three (biologically plausible) techniques: Reservoir Computing (RC), Slow Feature Analysis (SFA), and...

A neural network model for the identification and classification of malign and benign skin lesions from ALAinduced fluorescence images is presented. A self-organizing feature map or generative topographic mapping is used to cluster images patches according to their inherent local features which then can be extracted with ICA. These components are used to distinguish skin cancer from benign lesi...

A geometric approach to data representation incorporating informationtheoretic ideas is presented. The task of finding a faithful representation, where the input distribution is evenly partitioned into regions of equal mass, is addressed. For input consisting of mixtures of statistically independent sources, we treat independent component analysis (ICA) as a computational geometry problem. Firs...

In this paper, we assume that word co-occurrence statistics can be used to extract meaningful features, exhibiting syntactic and semantic behavior, from text data. Independent component analysis (ICA), an unsupervised statistical method, is applied to word usage statistics, calculated from a natural language corpora, to extract a number of features. With a self-organizing map (SOM), we will dem...

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Guided by the principles of geometric independent component analysis (ICA), we present a new approach (SOMICA) to linear geometric ICA using a self-organizing map (SOM). We observe a considerable improvement in separation quality of different distributions, albeit at high computational costs. The SOMICA algorithm is therefore primarily interesting from a theoretical point of view bringing toget...