Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using M...
Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using Multi-Omics Analysis and the Opade AI Prediction Tools
About this item
Full title
Author / Creator
Corrivetti, Giulio , Monaco, Francesco , Vignapiano, Annarita , Marenna, Alessandra , Palm, Kaia , Fernández-Arroyo, Salvador , Frigola-Capell, Eva , Leen, Volker , Ibarrola, Oihane , Amil, Burak , Caruson, Mattia Marco , Chiariotti, Lorenzo , Palacios-Ariza, Maria Alejandra , Hoekstra, Pieter J , Chiang, Hsin-Yin , Floareș, Alexandru , Fagiolini, Andrea and Fasano, Alessio
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
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More information
Scope and Contents
Contents
According to the World Health Organization (WHO), major depressive disorder (MDD) is the fourth leading cause of disability worldwide and the second most common disease after cardiovascular events. Approximately 280 million people live with MDD, with incidence varying by age and gender (female to male ratio of approximately 2:1). Although a variety...
Alternative Titles
Full title
Optimizing and Predicting Antidepressant Efficacy in Patients with Major Depressive Disorder Using Multi-Omics Analysis and the Opade AI Prediction Tools
Authors, Artists and Contributors
Author / Creator
Monaco, Francesco
Vignapiano, Annarita
Marenna, Alessandra
Palm, Kaia
Fernández-Arroyo, Salvador
Frigola-Capell, Eva
Leen, Volker
Ibarrola, Oihane
Amil, Burak
Caruson, Mattia Marco
Chiariotti, Lorenzo
Palacios-Ariza, Maria Alejandra
Hoekstra, Pieter J
Chiang, Hsin-Yin
Floareș, Alexandru
Fagiolini, Andrea
Fasano, Alessio
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_9100a1368e0f4dd58714b584246ff9d2
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9100a1368e0f4dd58714b584246ff9d2
Other Identifiers
ISSN
2076-3425
E-ISSN
2076-3425
DOI
10.3390/brainsci14070658
