A psychometric study was conducted in order to collect basic information about post-event processing in social anxiety. It was found that such processing occurs commonly after an anxiety-evoking or embarrassing social event and post-event processing scores were significantly correlated (r = 0.40) with social anxiety. The recollections of the social event tended to be recurrent and intrusive, in...

In this article, the latent class analysis framework for modeling single event discrete-time survival data is extended to low-frequency recurrent event histories. A partial gap time model, parameterized as a restricted factor mixture model, is presented and illustrated using juvenile offending data. This model accommodates event-specific baseline hazard probabilities and covariate effects; even...

INTRODUCTION Data about treatments and recurrent ischemic events in patients surviving their most recent myocardial infarction event-free for at least 12 months are scarce. METHODS In a retrospective data analysis, charts of patients who had a myocardial infarction 1-3 years ago with an event-free period of at least 12 months after the index event and at least one high risk factor were centra...

BACKGROUND Traditional methods for analyzing clinical and epidemiological cohort study data have been focused on the first occurrence of a health outcome. However, in many situations, recurrent event data are frequently observed. It is inefficient to use methods for the analysis of first events to analyse recurrent event data. METHODS We applied several semi-parametric proportional hazards mo...

OBJECTIVES This study sought to examine the risk of major cardiac adverse events and death in a nationwide cohort of patients without previous comorbidity admitted for syncope. BACKGROUND Syncope is a common clinical event, but knowledge of prognosis is not fully elucidated in healthy individuals. METHODS Patients without previous comorbidity admitted for syncope in Denmark from 2001 to 200...

Abstract This paper investigates the event-based state estimation for discrete-time recurrent delayed semi-Markovian neural networks. An event-triggering protocol is introduced to find measurement output with a specific triggering condition so as lower burden of data communication. A novel summation inequality established existence asymptotic stability error system. The problem addressed here c...

Rare sound event detection is a newly proposed task in IEEE DCASE 2017 to identify the presence of monophonic sound event that is classified as an emergency and to detect the onset time of the event. In this paper, we introduce a rare sound event detection system using combination of 1D convolutional neural network (1D ConvNet) and recurrent neural network (RNN) with long shortterm memory units...

BACKGROUND In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g. the beginning of some disease, in contrast to a gap time scale where the hazard process restarts after each event. While techniques such as the Andersen-Gill mode...