Project description
Using AI to predict disease progression in Parkinson’s disease
Parkinson’s disease is a neurological condition expected to double in prevalence by 2050. The disease progresses very differently between individuals, making personalised treatment planning and early intervention extremely challenging. AI offers a powerful opportunity to identify patterns in complex clinical data that predict individual disease trajectories. With the support of the Marie Skłodowska-Curie Actions programme, the mAIcompass project aims to develop an AI application that integrates longitudinal clinical and imaging data to predict motor, cognitive and neuropsychiatric decline in individual patients. The tool will be trained on one of the world’s largest Parkinson’s disease datasets and validated by clinicians and patients, providing a roadmap for personalised disease management and improved treatment outcomes.
Objective
Parkinson’s Disease (PD) is the fastest-growing neurological condition with global cases estimated to double to 20M by 2050. The spectrum, onset and progression of PD symptoms are highly heterogeneous between individuals, hampering treatment personalization through early prediction of disease course. I aim to develop mAIcompass; a multimodal AI-based clinical application, that leverages longitudinal clinical and imaging data, acquired during follow-up examinations, to facilitate real-time prognostication of PD progression, in terms of motor function deterioration, cognitive decline and neuropsychiatric impairment. It will also aid the early prediction of the overall progression subtype, based on neurobiological phenotypes of PD subgroups with similar progression pattern, identified through temporal clustering. The fellowship will be hosted by the Neuropsychiatry team of Amsterdam UMC that leads ENIGMA PD consortium, the largest existing international collection of PD datasets. I will leverage advanced expertise to develop novel algorithms for longitudinal PD data modelling and subtyping at the Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania (outgoing phase). Upon validation of expert clinicians and engineers, I will integrate the AI models into a user-friendly standalone application software intended for educational, research and experimental clinical use. Feedback for its utility will be obtained from end-users and patients focus groups at a PD clinical center. These tasks will set a roadmap for mAIcompass future clinical implementation, that is expected to aid the personalized PD clinical management, towards maximizing patients’ treatment benefit and reducing healthcare costs, proportionally varying with PD progression. mAIcompass aspires to link its expected scientific, societal and economic impacts to the Parkinson’s Manifesto for Europe, as well as to EU priorities emphasizing promotion of citizens' health and well-being.
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Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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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
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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-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
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(opens in new window) HORIZON-MSCA-2025-PF
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1081 HV Amsterdam
Netherlands
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