US DE COOKIES
Utilitzem cookies necessaries de sistema pel correcte funcionament de la web i cookies opcionals de Google Analytics per obtenir estadístiques de visita (sense obtenir dades personales). + Info
Acceptar cookies

Título

Predicting diagnosis on first-episode psychosis through fingerprints, genomics and deep learning algorithms

Resumen

The general aim of our project is to contribute to the identification of biologically informed markers with direct applicability for early detection and diagnostic precision of psychotic disorders. Starting from a fingerprint-based algorithm that we have developed previously through machine learning methods, wem propose to combine biometric anf genetic markers to generate a multimodal biomarker with discriminant potential for psychotic disorders. Clinical interviews will remain central to the diagnosis of psychotic disorders, but the out come of this proposal could bring a new tool to help establish sooner a precise diagnosis, which is a major clinical need intrinsically related to improving the disorder treatment and prognosis.

Financiador

CIBERSAM ISCIII - Intramural

Importe de la ayuda

15.000 €

 

Formem part de
HH Província Espanya
Contacteu-nos

Avda. Jordà , 8 - 08035 Barcelona
Telèfon: 93 548 01 05
E-mail: fundacio@fidmag.com
Formulari de contacte online 

         

 

Reconeixements a la qualitat i l'excel·lència
Darrera modificació: 27/09/2022
AGAUR
CIBERSAM
Generalitat de Catalunya
ISCIII
Logo UE 2022
MICINN