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CORDIS

Artificial intelligence-based Parkinson’s disease risk assessment and prognosis

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Study initiation package (dBM-DEV study) (opens in new window)

Package including the clinical study registration number in a registry meeting WHO criteria, final version of the approved study protocol, and regulatory/ethics approvals required for the enrolment of the first study participant.

Dissemination, communication and exploitation plan (opens in new window)

The dissemination, communication and exploitation strategy (including stakeholders’ analysis), plans, language, and impact evaluation.

Initial report on domain review and datasets (opens in new window)

Initial (early R&D) report on domain review and existing, relevant health databases/sets and biobanks.

First report on predictive modelling for PD (opens in new window)

Report on early genetic profiling and early versions of predictive models for PD risk, progression, and medication response prediction, including, i.a., datasets used, methods, benchmarking, and internal validation evidence.

First report on digital biomarkers for PD (opens in new window)

Report on the early versions of dBMs for tracking key PD risk and progression markers, the associated technology, development/ implementation process, and validation or verification evidence.

Trustworthy AI development and evaluation framework (fundamental version) (opens in new window)

Fundamental compilation of guidelines for building trustworthy AI and report on relevant procedures, tools and developed metrics to be adopted for developing the AI-driven components and evaluating their performance (with emphasis on accuracy, reliability, reproducibility and generalisability).

Midterm recruitment report (dBM-DEV study) (opens in new window)

Report including an overview of the number of participants recruited by clinical sites, any recruitment problems, and a detailed description of implemented and planned measures to compensate for any incurred delays.

Initial report on user research and co-creation (opens in new window)

Initial (before R&D initiation) report on the methods, implementation and outputs of user research and co-creation processes, including empathy/journey maps and user stories/requirements.

First report on project visibility and educational material (opens in new window)

Periodic report on project visibility (dissemination, communication, and networking activities), including impact indicators, and the educational content developed.

The AI-PROGNOSIS digital health ecosystem (Alpha version) (opens in new window)

Alpha version (individual components) of the mAI-[Health, Care, Insights] apps, and companion report on features, deployment (including AI) and performance.

Project branding and communication channels (opens in new window)

Presentation of the project’s visual identity, website, social media channels and communication kit.

Publications

Assessing motor skills in Parkinson's Disease using smartphone-based video analysis and machine learning (opens in new window)

Author(s): Andreas Stergioulas, Sofia Dias, Beatriz Alves, Ghada Al Hussein, Sevasti Bostantjopoulou, Zoe Katsarou, Ioannis Dagklis, Nikos Grammalidis, Kosmas Dimitropoulos
Published in: Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments, 2024
Publisher: ACM
DOI: 10.1145/3652037.3663945

MoveONParkinson: developing a personalized motivational solution for Parkinson’s disease management (opens in new window)

Author(s): Beatriz Alves, Pedro R. Mota, Daniela Sineiro, Ricardo Carmo, Pedro Santos, Patrícia Macedo, João Casaca Carreira, Rui Neves Madeira, Sofia Balula Dias, Carla Mendes Pereira
Published in: Frontiers in Public Health, Issue 12, 2024, ISSN 2296-2565
Publisher: Frontiers Media SA
DOI: 10.3389/fpubh.2024.1420171

Bispectral Analysis of Parkinsonian Rest Tremor: New Characterization and Classification Insights Pre-/Post-DBS and Medication Treatment (opens in new window)

Author(s): Ioannis Ziogas, Charalampos Lamprou, Leontios J. Hadjileontiadis
Published in: IEEE Access, Issue 11, 2023, ISSN 2169-3536
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/ACCESS.2023.3324987

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