BACKGROUND Existing studies of childhood dilated cardiomyopathy deal mainly with early survival. This population-based study examines long-term outcomes for children with dilated cardiomyopathy. METHODS AND RESULTS The diagnosis of dilated cardiomyopathy was based on clinical, echocardiographic, and pathological findings. The primary study end point included time to the combined outcome of de...

It has been shown that the authentication performance of a biometric system is dependent on the models/templates specific to a user. As a result, some users may be more easily recognized or impersonated than others. The various categories of users have been characterized by Doddington et al.(1988). We refer to this unbalanced performance across users as the Doddington’s zoo effect. In the conte...

Objective(s): Alternative normalization methods were proposed to solve the biased information of SPM in the study of neurodegenerative disease. The objective of this study was to determine the most suitable count normalization method for SPM analysis of a neurodegenerative disease based on the results of different count normalization methods applied on a prepared digital phantom similar to one ...

In this paper, we propose a novel method of normalizing the voice quality in an utterance for both clean speech and speech contaminated by noise. The normalization method is applied to the N-best hypotheses from an HMM-based classifier, then an SM (Sub-space Method)-based verifier tests the hypotheses after normalizing the monophone scores together with the HMMbased likelihood score. The HMM-SM...

The Center for Science and Technology Studies at Leiden University advocates the use of specific normalizations for assessing research performance with reference to a world average. The Journal Citation Score (JCS) and Field Citation Score (FCS) are averaged for the research group or individual researcher under study, and then these values are used as denominators of the (mean) Citations per pu...

We introduce an end-to-end system capable of named-entity detection, normalization and relation extraction for extracting information about bacteria and their habitats from biomedical literature. Our system is based on deep learning, CRF classifiers and vector space models. We train and evaluate the system on the BioNLP 2016 Shared Task Bacteria Biotope data. The official evaluation shows that ...

The lack of robustness against image quality degradation is a open issue in fingerprint verification. It has been found in previous studies that the behavior of a fingerprint verification system may vary depending on the quality of the fingerprints. In this paper, we study the performance for individual users under varying image conditions using a multisensor database acquired with three differ...

Gene/protein recognition and normalization is an important preliminary step for many biological text mining tasks. In this paper, we present a multistage gene normalization system which consists of four major subtasks: pre-processing, dictionary matching, ambiguity resolution and filtering. For the first subtask, we apply the gene mention tagger developed in our earlier work, which achieves an ...

Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then has to resort to Markov Chain Monte Carlo methods, or approximations of the normalization constant. Previously, a method called score matching was proposed for computationally efficient yet (locally) consistent estimation...

In this paper we present the main advances of the IRISA speech group from 2001 to 2004 in robust methods for Bayesian adaptation of speaker models and Bayesian decision. The probabilistic framework and the state-of-the-art Bayesian approach for automatic speaker verification are first recalled. We then describe two original contributions for robust Bayesian decision. The first one is a score no...