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Predicting individual improvement in schizophrenia symptom severity at 1‐year follow‐up: Comparison of connectomic, structural, and clinical predictors
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1‐year follow‐up was assessed in 30 indi...
Zapisane w:
| Wydane w: | Hum Brain Mapp |
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| Główni autorzy: | , , , , , , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
John Wiley & Sons, Inc.
2020
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7375115/ https://ncbi.nlm.nih.gov/pubmed/32469448 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/hbm.25020 |
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