Project description
AI advances Parkinson’s disease diagnosis
Parkinson's disease (PD) is characterised by the progressive loss of dopamine-producing brain cells, leading to diverse motor and non-motor symptoms. PD is often missed or misdiagnosed as early signs are subtle and common with other diseases, while selecting the optimal treatment is usually a lengthy process, leading to unnecessary suffering. Funded by the Horizon Europe programme, the AI-PROGNOSIS project aims to advance PD diagnosis and care by harnessing the power of AI. The consortium will develop predictive models for PD risk and prognosis based on in-depth health and genetic data and combine them with specific biomarkers measured in everyday life. Project work will lead to the creation of a digital health toolkit offering persons affected by PD and healthcare professionals valuable insights for informed health management.
Objective
Parkinson’s disease (PD) is the most common neurodegenerative movement disorder, with a multifactorial aetiology, heterogeneous manifestation of motor and non-motor symptoms, and no cure. PD is often missed or misdiagnosed, as early symptoms are subtle and common with other diseases, allowing for considerable damage to occur before treatment. Moreover, selecting the optimal medication regimen is usually a lengthy, “trial and error” process, leading to critical, costly non-adherence. Following a trustworthy and inclusive approach to AI development and based on multidisciplinary expertise and broad stakeholder engagement, AI-PROGNOSIS aims to advance PD diagnosis and care by: 1) developing novel, predictive AI models for personalised PD risk assessment and prognosis (in terms of time to higher disability transition and response to medication) based on multi-source patient records and databases, including in-depth health, phenotypic and genetic data, 2) implementing a system of biomarkers informing the AI models by tracking key risk/progression markers in daily living, and ultimately 3) translating the models and digital biomarkers into a validated, privacy-aware AI-driven toolkit, supporting healthcare professionals (HCPs) in disease screening, monitoring and treatment optimization via quantitative, explainable evidence, and empowering individuals with/without PD with tailored insights for informed health management.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.1 - Health
MAIN PROGRAMME
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HORIZON.2.1.1 - Health throughout the Life Course
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-RIA - HORIZON Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-HLTH-2022-STAYHLTH-01-two-stage
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546 36 THESSALONIKI
Greece
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Participants (15)
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3001 Leuven
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1253 Luxembourg
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152 32 ATHINA
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751 05 Uppsala
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65205 Wiesbaden
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31052 TOULOUSE CEDEX 3
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1495-688 Cruz Quebrada Lisboa
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570 01 THERMI THESSALONIKI
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86633 Neuburg An Der Donau
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3000 Leuven
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
1000 Bruxelles / Brussel
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
01069 Dresden
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
LV-1050 RIGA
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
2371 AGIOS DOMETIOS
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28002 Madrid
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Partners (3)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
Participation ended
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WC2R 2LS London
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OX1 2JD Oxford
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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E1 4NS LONDON
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