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RETENTION

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Cerrado

heaRt failurE paTient managEment and iNTerventIOns usiNg continuous patient moni...

heaRt failurE paTient managEment and iNTerventIOns usiNg continuous patient monitoring outside hospitals and real world data Heart failure (HF) is a prominent chronic disease, despite efforts in improving its prevention, diagnosis and treatment, represents the leading cause of disability and premature death throughout the world, while being is a heavy b... ver más

30/04/2025

RESEARCH UNIVERSIT...

6M€

Presupuesto del proyecto: 6M€

Líder del proyecto

EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMAT... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 16 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-01-22

SC1-DTH-12-2020: Use of Real-World Data to advance r... Specific Challenge:The number of people with chronic illness is growing and almost half of them have...

I+D

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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

16 Participantes

RESEARCH UNIVERSITY INSTITUT...

445.50K€ | Lider

DATAMED

390.25K€ | Participante

UNIBO

725.37K€ | Participante

AEGIS IT RESEARCH GMBH

353.75K€ | Participante

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Duración del proyecto: 51 meses Fecha Inicio: 2021-01-22
Fecha Fin: 2025-04-30

Líder del proyecto

EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMAT... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 6M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Heart failure (HF) is a prominent chronic disease, despite efforts in improving its prevention, diagnosis and treatment, represents the leading cause of disability and premature death throughout the world, while being is a heavy burden on health systems due to the multiple, prolonged hospitalizations required for patients suffering from it and the related management costs. Nevertheless, studies have shown that routine patient-physician or patient-nurse communication following discharge can result in significant reduction of hospitalizations. The pertinent collected patient data may include simple yet important information (e.g. patient weight), as well as previously difficult to obtain information such as routine ECG, ICD/CRT-D interrogation and pulmonary arterial pressure monitoring, which are now within reach due to technological progress. Motivated by the above, RETENTION aims to develop and deliver an innovative platform supporting enhanced clinical monitoring and interventions aimed at improving the clinical management of patients with chronic HF, reducing their mortality and hospitalisation rates, and improving their quality of life, safety, and well-being. The RETENTION platform will support clinical decision making and evidenced based personalised interventions for HF patients by: (a) continually monitoring and collecting medical, clinical, physiological, behavioural, psychosocial, and real-world data for such patients, (b) analysing these data using innovative model-driven big data analytics, statistical, artificial intelligence and machine learning techniques, (c) detecting patterns in the HF disease progression and the quality of life of patients, (d) cross checking and validating them against the clinical literature, and (e) offering transparent, explainable and verifiable decision making capabilities that leverage the evidence produced by the underlying data analysis and augment clinical studies targeting HF and other CVDs.

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