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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 €

 

We are part of
HH Província España
Contact us

Avda. Jordà , 8 - 08035 Barcelona
Contact phone: 93 548 01 05
E-mail: fundacio@fidmag.com
Online contact 

         

 

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Última modificación: 05/12/2022
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CIBERSAM
Generalitat de Catalunya
ISCIII
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