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AI4LUNGS

Financiado

AI-BASED PERSONALISED CARE FOR RESPIRATORY DISEASE USING MULTI-MODAL DATA IN PAT...

AI-BASED PERSONALISED CARE FOR RESPIRATORY DISEASE USING MULTI-MODAL DATA IN PATIENT STRATIFICATION AI4Lungs will develop and validate novel AI-based tools and computational models to improve patient stratification optimising diagnosis and treatment of infectious and non-infectious respiratory diseases. Diagnosis of respiratory... ver más

30/06/2027

INESC TEC

7M€

Presupuesto del proyecto: 7M€

Líder del proyecto

INESC TEC INSTITUTO DE ENGENHARIADE SISTEMAS... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Ver 18 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-12-07

HORIZON-HLTH-2022-TOOL-12-01-two-stage: Computational models for new patien... ExpectedOutcome:This topic aims at supporting activities that are enabling or contributing to one or...

I+D

Cerrada hace 2 años

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18 Participantes

INESC TEC

1.25M€ | Lider

MOR RESEARCH APPLICATIONS LT...

403.50K€ | Participante

Innovasjon Norge

193.13K€ | Participante

FUNDACIO PRIVADA INSTITUT D'...

223.09K€ | Participante

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Duración del proyecto: 42 meses Fecha Inicio: 2023-12-07
Fecha Fin: 2027-06-30

Líder del proyecto

INESC TEC INSTITUTO DE ENGENHARIADE SISTEMAS... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 7M€

Descripción del proyecto AI4Lungs will develop and validate novel AI-based tools and computational models to improve patient stratification optimising diagnosis and treatment of infectious and non-infectious respiratory diseases. Diagnosis of respiratory disease comprises a complex assessment of several multiple exams over time that together characterise the patient condition. Streamlined into existing clinical pathways, AI4Lungs will support clinicians and other stakeholders in decision making along the patient journey from initial suspicion to diagnosis, and treatment planning. The models incorporate clinical partners’ multiple data sources, registries and open national/international databases, including multiple data types from medical records, imaging data as well as novel data from digital stethoscope and –omics. AI4Lungs stratification strategy will build computational models employing structured and unstructured data modalities, leading to more accurate positioning of patients and enabling them to benefit from global data and knowledge shared during all stages of care, focusing on diagnosis and treatment planning. With scale up, AI4Lungs will support any patient from any country, any hospital no matter how remote or small, by stratifying them among all of Europe’s patients from that cluster, gaining access to the collective expertise, experience and information on optimal care options. In parallel, health systems will reduce costs and effort in unnecessary testing, ineffective treatments and emergency services, optimizing use of health technologies and resources. AI4Lungs patient stratification tools will focus on respiratory diseases, a complex and broad set of disorders with high disease burden. AI and real world data combined with innovative holistic diseases modelling, will offer a solution for allocating resources more efficiently, making best treatment pipelines accessible to more patients while complying with FAIR principles and relevant regulatory and ethical guidelines.

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