THE BAYESIAN VIRTUAL EPILEPTIC PATIENT: A PROBABILISTIC FRAMEWORK DESIGNED TO INFER THE SPATIAL MAP OF EPILEPTOGENICITY IN A PERSONALIZED LARGE-SCALE BRAIN MODEL OF EPILEPSY SPREAD

Despite the importance and frequent use of Bayesian frameworks in brain network modeling for parameter inference and model prediction, the advanced sampling algorithms implemented in probabilistic programming languages to overcome the inference difficulties have received relatively little attention in this context.In this technical note, we propose

Background: The recent Ebola virus disease (EVD) outbreak has been described as unprecedented in terms of morbidity, mortality, and geographical extension.It also revealed many weaknesses and inadequacies for disease surveillance and response systems in Africa due to underqualified staff, cultural beliefs, and lack of trust for the formal health ca

This study aimed to analyze accounts of nurses who undertake the dressing of fungating wounds of women with breast cancer, and to outline contributions to the nursing care.This is qualitative research, carried out in November 2010 with interviews and thematic analysis involving five nurses from the outpatient department of a public hospital in the

ContextEye tracking is a technology to measure and determine the eye movements and eye positions of an individual.The eye data can be collected and recorded using an eye tracker.Eye-tracking data offer unprecedented insights into human actions and environments, digitizing how people communicate with computers, and providing novel opportunities to c

Introduction: This study was aimed to compare of the effectiveness of group cognitive-behavioral therapy and methadone maintenance therapy on changing beliefs toward substance abuse among addicted people.Method: The research method was a quasi-experimental 517 pretest-posttest with witness group.30 addicted people who were referred to the addiction