1,721,007 research outputs found
Learning proficiency and brain structure: systematic brain-behavior relationships in controls but not in patients with schizophrenia or bipolar disorder
No full textLearning proficiency and brain structure: systematic brain-behavior relationships in controls but not in patients with schizophrenia or bipolar disorde
Increased hypothalamus and mammillary bodies volumes in chronic schizophrenia
No full textIncreased hypothalamus and mammillary bodies volumes in chronic schizophreni
More severe prefrontal abnormalities in poor outcome (Kraepelinian) schizophrenia
No full textMore severe prefrontal abnormalities in poor outcome (Kraepelinian) schizophreni
Selecting scales by multiple kernel learning for shape diffusion analysis
No full textBrain morphological abnormalities can typically be detected by advanced geometrical shape analysis techniques. Recently, shape diffusion methods have proved to be very effective in providing useful descriptions for brain classification purposes. In particular, they allow the analysis of such shapes at multiple scales, but the selection of the correct range of scales remains an open issue heavily affecting the performance of methods, and it needs to be estimated adaptively for different classes of shapes. In this paper, we focus on the diffusion scale selection in order to define a robust shape descriptor for brain classification. To this end, geometric features are extracted for each scale and the best feature combination is selected by employing \it multiple kernel learning (MKL). In the presented experiments, we compare the shape of Thalamic regions in order to discriminate between normal subjects and schizophrenic patients. We demonstrate that MKL allows to obtain classifiers which are more accurate with respect to other competing algorithms for schizophrenia detection. Moreover, using the weights computed by the MKL algorithm, we can select at which scale the features are more effective for schizophrenia classification
Specific linguistic and pragmatic deficits in Italian patients with schizophrenia
No full textOBJECTIVE:Verbal communication impairments are prominent features of schizophrenia. The grammatical and pragmatic components of expressive and receptive verbal abilities were systematically examined, for the first time, in Italian patients with schizophrenia. Indeed, most of the language literature is composed of studies on English speaking people.METHOD:Elicited narrative production, and syntactic and pragmatic receptive abilities were analyzed in a cohort of 37 patients with schizophrenia and 37 healthy controls. Furthermore, a conversational speech production task was administered to an age- and gender-matched subset of this population. The level of significance was set at
Dealing with multigranular spatio-temporal databases to manage psychiatric epidemiology data
No full textIn epidemiology spatio-temporal data may represent surveillance data and origins of diseases. In order to better exploit these data, temporal and spatial dimensions could be managed considering them as meta-data useful to retrieve classical data. In this paper, we propose to use a framework for spatio-temporal granularities with the aim to improve the querying of clinical spatio-temporal data. We show how granularities can be used to enrich a psychiatric case register. We exemplify our approach reporting spatio-temporal queries, based on granularities, useful for epidemiological studies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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