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Deficits in working memory (WM) are a consistent neurocognitive marker for schizophrenia. Previous studies have suggested that WM is the product of coordinated activity in distributed functionally connected brain regions. Independent component analysis (ICA) is a data-driven approach that can identify temporally coherent networks that underlie fMRI(More)
Children and adolescents who develop schizophrenia tend to have greater symptom severity than adults who develop the illness. Since the brain continues to mature into early adulthood, developmental differences in brain structure and function may provide clues to the underlying neurobiology of schizophrenia. With an emerging body of evidence supporting(More)
We introduce the nonparametric meta-data dependent relational (NMDR) model, a Bayesian nonparametric stochastic block model for network data. The NMDR allows the entities associated with each node to have mixed membership in an unbounded collection of latent communities. Learned regression models allow these memberships to depend on, and be predicted from,(More)
Stochastic block models characterize observed network relationships via latent community memberships. In large social networks, we expect entities to participate in multiple communities, and the number of communities to grow with the network size. We introduce a new model for these phenomena, the hierarchical Dirichlet process relational model, which allows(More)
A number of recent studies have combined multiple experimental paradigms and modalities to find relevant biological markers for schizophrenia. In this study, we extracted fMRI features maps from the analysis of three experimental paradigms (auditory oddball, Sternberg item recognition, sensorimotor) for a large number (n=154) of patients with schizophrenia(More)
We introduce a new variational inference objective for hierarchical Dirichlet process ad-mixture models. Our approach provides novel and scalable algorithms for learning nonparametric topic models of text documents and Gaussian admixture models of image patches. Improving on the point estimates of topic probabilities used in previous work, we define full(More)
OBJECTIVE Previous studies have shown that patients with schizophrenia have less modulation of the task-positive and default mode neural networks during novelty detection. The diminished modulation may be interpreted as less functional activation of the task-positive network and less functional deactivation of the default mode network. The relationship(More)
PURPOSE This study aimed to determine the optimal initial vancomycin dose to achieve appropriate trough levels in pediatric patients. METHODS We analyzed clinical data for 309 children treated with intravenous vancomycin between 2004 and 2009 at 2 different hospitals in South Korea. The patients were 1-16 years old and exhibited normal renal function.(More)
We report a 65 year-old man with a large cystic phyllodes tumor of the prostate. The patient complained of abdominal discomfort and had a soft palpable mass. Computer tomography showed a solid and cystic mass in the pelvic fossa; the mass was adjacent only to the prostate. We excised the mass. Microscopic findings of the mass showed hyperplastic epithelium(More)