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  1. Pubblicazioni

NEUROSCIENCE APPLIED

Rivista
Codice:
E265425
ISSN:
2772-4085
  • Dati Generali

Dati Generali

Pubblicazioni (14)

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A machine learning pipeline for efficient differentiation between bipolar and major depressive disorder based on multimodal structural neuroimaging
Articolo
A machine learning pipeline for efficient differentiation between depressed bipolar disorder and major depressive disorder patients based on structural neuroimaging
Abstract
Breaking free from the inflammatory trap of depression: Regulating the interplay between immune activation and plasticity to foster mental health
Articolo
Cognitive distortions and structural neuroimaging data predict depression severity in unipolar and bipolar depression: a machine learning study
Abstract
Combining clinical data, genetics, and adverse childhood experiences for suicidality prediction in mood disorders: a machine learning approach
Abstract
Data-driven stratification of depressed patients based on structural neuroimaging signatures: a stability-based relative clustering validation approach
Abstract
Functional neuroimaging for the differentiation between healthy controls, depressed bipolar and major depressive patients: a machine learning study
Abstract
Identifying suicide attempters among bipolar depressed patients using structural neuroimaging: a machine learning study
Abstract
Immune-inflammation and structural neuroimaging differentiate bipolar and unipolar depression: a machine learning study
Abstract
Machine learning signature in differentiating bipolar and unipolar depression with multimodal structural neuroimaging data and neuropsychology
Abstract
Moving beyond clinical approaches: machine learning on neuroimaging and cognitive features for the differential diagnosis between unipolar and bipolar depression
Contributo in Atti di convegno
Predicting cognitive impairment in depression: a machine learning approach on multimodal structural neuroimaging
Abstract
Prediction of cognitive impairment in mood disorders using multimodal structural neuroimaging: a machine learning study
Abstract
Unsupervised neurobiologically-driven stratification of clinical heterogeneity in treatment-resistant depression
Articolo
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