OBJECTIVE: Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integratio...
Why some individuals, when presented with unstructured sensory inputs, develop altered perceptions not based in reality, is not well understood. Machine learning approaches can potentially help us understand how the brain normally interprets sensory ...
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging ...
Annals of the New York Academy of Sciences
Nov 10, 2016
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...
BACKGROUND: Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differe...
Recently, an increasing number of researchers have endeavored to develop practical tools for diagnosing patients with schizophrenia using machine learning techniques applied to EEG biomarkers. Although a number of studies showed that source-level EEG...
BACKGROUND: A structural neuroanatomical change indicating a reduction in brain tissue is a notable feature of schizophrenia. Several pathophysiological processes such as aberrant cortical maturation, progressive tissue loss and compensatory tissue i...
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...
OBJECTIVE: Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a ...
Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiolo...