Hola,
¿eres nuevo aquí?

Regístrate gratis y conecta tu empresa con financiación pública, partners y proyectos.

Tengo cuenta

Regístrate

Ver video

ARTEMIS

Financiado

Cerrado

Assessment of Reserve Translational Evaluation of Medical Images and Statistics...

Assessment of Reserve Translational Evaluation of Medical Images and Statistics Prediction models for outcomes of brain health Stroke and cognitive decline are among the leading contributors to disease burden and long-term disability worldwide. Despite their prevalence, the contributing disease processes are not fully understood. This is in part due to th... ver más

31/05/2020

BUNDESMINISTERIUM...

240K€

Presupuesto del proyecto: 240K€

Líder del proyecto

BUNDESMINISTERIUM FUER GESUNDHEIT No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 3 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-05-31

MSCA-IF-2016: Individual Fellowships

I+D

Cerrada hace 8 años

0% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

BUNDESMINISTERIUM FUER GESUN...

239.86K€ | Lider

THE GENERAL HOSPITAL CORPORA...

160.13K€ | Participante

Proyectos interesantes

VPH-DARE@IT

Medical Technol...

Data Science

18M€ Cerrado

PRE2018-083507

Medical Technol...

Data Science

93K€ Cerrado

DPI2017-86696-R

Medical Technol...

Data Science

218K€ Cerrado

PID2020-118386RA-I00

Medical Technol...

Data Science

33K€ Cerrado

TIN2016-80347-R

Medical Technol...

Data Science

146K€ Cerrado

BID

Medical Technol...

Data Science

556K€ Cerrado

Conecta tu I+D

¿Tienes un proyecto y buscas un partner? Gracias a nuestro motor inteligente podemos recomendarte los mejores socios y ponerte en contacto con ellos. Te lo explicamos en este video

Duración del proyecto: 38 meses Fecha Inicio: 2017-03-09
Fecha Fin: 2020-05-31

Líder del proyecto

BUNDESMINISTERIUM FUER GESUNDHEIT No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 240K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Stroke and cognitive decline are among the leading contributors to disease burden and long-term disability worldwide. Despite their prevalence, the contributing disease processes are not fully understood. This is in part due to the lack of (early) prediction models and ways to characterize protective mechanisms, which can help to distinguish between patients and healthy individuals before symptoms manifest. Such prediction models can facilitate prevention strategies for adverse cognitive and functional outcomes, thereby enriching patients’ life quality and reduce the economic burden on society. Advanced neuroimaging techniques, such as MRI, have provided additional insight into the underlying disease biology. One major challenge when using neuroimaging techniques lies in the fact that large amounts of data are required to account for variations in clinical presentation and assessment, necessitating the use of dedicated pipelines for extracting phenotypes. However, most pipelines are developed in research settings and tend to fail when applied to real-life clinical cohorts, leading to a subpar use of rich, available patient datasets. Here, a fully-automated, translational pipeline for extracting MRI phenotypes from data acquired in clinical and research settings is developed with a particular focus on outlining white matter hyperintensities (WMH). WMH are a common phenotype in aging and across diseases; however, group differences are poorly understood. This makes WMH a prime candidate for extracting additional information, which can be used for outcome prediction. The proposed prediction models utilize newly extracted characteristics, clinical/demographic information and a latent variable construct to predict general cognitive decline and outcome after stroke. In particular, the proposed latent variable has shown promise in acting as a surrogate measure for protective mechanisms in stroke patients, where its biological meaning is assessed as part of this project.

Conecta tu I+D

Entra hoy

¿Olvidé mi contraseña?

Financiación

Empresas

CTIs/Universidades

Proyectos

Investigadores