693 research outputs found
White matter alterations in early stages of schizophrenia: A systematic review of diffusion tensor imaging studies
No full textSeveral lines of evidence suggest that the normal integration of cerebral communication may be compromised in schizophrenia, with white matter (WM) abnormalities being integral to these functional deficits. Diffusion tensor imaging (DTI) is a neuroimaging technique which has increasingly been used to study WM through quantitative indices of its structural and orientational characteristics. Identifying the WM differences early in the course of schizophrenia may assist in prevention, early diagnosis and identification of treatment targets. In that respect, the aims of the present study were to (a) systematically review WM integrity in the early stages of schizophrenia as inferred by DTI and (b) specifically examine parameters that may affect WM: age, duration of illness and treatment. In summary, DTI studies in early schizophrenia suggest that structural dysconnectivity may be already present in recent-onset and drug-naïve patients, as well as in individuals clinically at high risk for developing schizophrenia. Although the pattern of WM differences is not totally consistent frontal, fronto-temporal and fronto-limbic connections, with tracts including the superior longitudinal fasciculus, cingulum bundle, uncinate fasciculus and corpus callosum seem to be affected. These differences may depend on the developmental stage of the subjects, the duration of illness and exposure to antipsychotic medication. © 2013 by the American Society of Neuroimaging
sj-pdf-1-gsj-10.1177_21925682211058158 – Supplemental Material for Research Practices and Needs Among Spine Surgeons Worldwide
No full textSupplemental Material, sj-pdf-1-gsj-10.1177_21925682211058158 for Research Practices and Needs Among Spine Surgeons Worldwide by Niccole Germscheid, Jason P. Y. Cheung, Marko H. Neva, F. Cumhur Öner, Brian K. Kwon, Marcelo Valacco, Waleed Awwad, Daniel M. Sciubba, Stephen J. Lewis, Laurence D. Rhines, Sangwook T. Yoon, Mauro Alini, Sibylle Grad, Charles Fisher and Dino Samartzis in Global Spine Journal</p
sj-pdf-2-gsj-10.1177_21925682211058158 – Supplemental Material for Research Practices and Needs Among Spine Surgeons Worldwide
No full textSupplemental Material, sj-pdf-2-gsj-10.1177_21925682211058158 for Research Practices and Needs Among Spine Surgeons Worldwide by Niccole Germscheid, Jason P. Y. Cheung, Marko H. Neva, F. Cumhur Öner, Brian K. Kwon, Marcelo Valacco, Waleed Awwad, Daniel M. Sciubba, Stephen J. Lewis, Laurence D. Rhines, Sangwook T. Yoon, Mauro Alini, Sibylle Grad, Charles Fisher and Dino Samartzis in Global Spine Journal</p
A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning
Get PDFZanutto D, Michalopoulos C, Chatzistefanou G-A, et al. A Water Futures Approach on Water Demand Forecasting with Online Ensemble Learning. In: The 3rd International Joint Conference on Water Distribution Systems Analysis &amp; Computing and Control for the Water Industry (WDSA/CCWI 2024). Basel Switzerland: MDPI; 2024: 60.This study presents a collaborative framework developed by the Water Futures team of researchers for the “Battle of the Water Demand Forecasting” challenge at the 3rd International WDSA-CCWI Joint Conference. The framework integrates an ensemble of machine learning forecasting models into a deterministic outcome consistent with the competition formulation. The water demand trajectory over a week exhibits complex overlapping patterns and non-linear dependencies to multiple features and time-dependent events that a single model cannot accurately predict. As such, the reconciled forecast from an ensemble of models exceeds the performance of the individual ones and exhibits higher stability across the weeks of the year and district metered areas considered
- …
