195 resultados para Fuzzy Persistent Poverty
Resumo:
Background: Substance misuse is a common comorbid problem in people presenting with first-episode psychosis and is associated with a poor short-term outcome.
Aims: The aim of this study is to examine differences in baseline characteristics and 1-year outcome between individuals with first-episode psychosis who have never misused substances, those who stop misusing substances after initial presentation and those who persistently misuse substances over the 1-year assessment period.
Method: Patients were recruited to the Northern Ireland First Episode Psychosis Study (n=272). Clinical assessments were performed at baseline and at 1 year (n=194) and data were collected from the case notes.
Results: Individuals with persistent substance misuse had more severe depression, more positive symptoms, poorer functional outcome and greater rates of relapse at 1 year than those who stopped and those who had never misused substances. There were no differences in outcome between people who had never misused substances and those who stopped misusing after presentation.
Conclusions: These results support assertive intervention targeted at comorbid substance misuse in individuals with first-episode psychosis.
Resumo:
In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.
