Better real-world health-data distributed analytics research platform
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In recent years, data-driven medicine has gained increasing importance in terms of diagnosis,
treatment, and research due to the exponential growth of healthcare data. The linkage of cross-
border health data from various sources, including genomics, and analysis via innovative
approaches based on artificial intelligence (AI) will enable a better understanding of risk factors,
causes, and the development of optimal treatment in different disease areas. Nevertheless, the
reuse of patient data is often limited to datasets available at a single medical centre. The main
reasons why health data is not shared across institutional borders rely on ethical, legal, and privacy
aspects and rules. Therefore, in order to (1) enable health data sharing across national borders,
(2) fully comply with present GDPR privacy guidelines / regulations and (3) innovate by pushing
research beyond the state of the art, BETTER proposes a robust decentralised privacy-preserving
infrastructure which... will empower researchers, innovators and healthcare professionals to exploit
the full potential of larger sets of multi-source health data via tailored made AI tools useful to
compare, integrate, and analyse in a secure, cost-effective fashion; with the very final aim of
supporting the improvement of citizen’s health outcomes. In detail, this interdisciplinary project
proposes the co-creation of 3 clinical use cases involving 7 medical centres located in the EU and
beyond, where sensitive patient data, including genomics, are made available and analysed in a
GDPR-compliant mechanism via a Distributed Analytics (DA) paradigm called the Personal Health
Train (PHT). The main principle of the PHT is that the analytical task is brought to the data provider
(medical centre) and the data instances remain in their original location. In this project, two
mature implementations of the PHT (PADME and Vantage6) already validated in real-world
scenarios will be fused together to build the BETTER platform.
Извор:
European Comission, Horizon Europe, 2024Финансирање / пројекти:
- Horizon Europe, 101136262
Напомена:
- Principal Investigator: Dr. Matteo Bregonzio, DATRIX
- Coordinator for IMGGE: Dr. Maja Stojiljković
- Duration period: 2024-2027
Колекције
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - GEN PY - 2024 UR - https://imagine.imgge.bg.ac.rs/handle/123456789/2307 AB - In recent years, data-driven medicine has gained increasing importance in terms of diagnosis, treatment, and research due to the exponential growth of healthcare data. The linkage of cross- border health data from various sources, including genomics, and analysis via innovative approaches based on artificial intelligence (AI) will enable a better understanding of risk factors, causes, and the development of optimal treatment in different disease areas. Nevertheless, the reuse of patient data is often limited to datasets available at a single medical centre. The main reasons why health data is not shared across institutional borders rely on ethical, legal, and privacy aspects and rules. Therefore, in order to (1) enable health data sharing across national borders, (2) fully comply with present GDPR privacy guidelines / regulations and (3) innovate by pushing research beyond the state of the art, BETTER proposes a robust decentralised privacy-preserving infrastructure which will empower researchers, innovators and healthcare professionals to exploit the full potential of larger sets of multi-source health data via tailored made AI tools useful to compare, integrate, and analyse in a secure, cost-effective fashion; with the very final aim of supporting the improvement of citizen’s health outcomes. In detail, this interdisciplinary project proposes the co-creation of 3 clinical use cases involving 7 medical centres located in the EU and beyond, where sensitive patient data, including genomics, are made available and analysed in a GDPR-compliant mechanism via a Distributed Analytics (DA) paradigm called the Personal Health Train (PHT). The main principle of the PHT is that the analytical task is brought to the data provider (medical centre) and the data instances remain in their original location. In this project, two mature implementations of the PHT (PADME and Vantage6) already validated in real-world scenarios will be fused together to build the BETTER platform. T2 - European Comission, Horizon Europe T1 - Better real-world health-data distributed analytics research platform UR - https://hdl.handle.net/21.15107/rcub_imagine_2307 ER -
@misc{ year = "2024", abstract = "In recent years, data-driven medicine has gained increasing importance in terms of diagnosis, treatment, and research due to the exponential growth of healthcare data. The linkage of cross- border health data from various sources, including genomics, and analysis via innovative approaches based on artificial intelligence (AI) will enable a better understanding of risk factors, causes, and the development of optimal treatment in different disease areas. Nevertheless, the reuse of patient data is often limited to datasets available at a single medical centre. The main reasons why health data is not shared across institutional borders rely on ethical, legal, and privacy aspects and rules. Therefore, in order to (1) enable health data sharing across national borders, (2) fully comply with present GDPR privacy guidelines / regulations and (3) innovate by pushing research beyond the state of the art, BETTER proposes a robust decentralised privacy-preserving infrastructure which will empower researchers, innovators and healthcare professionals to exploit the full potential of larger sets of multi-source health data via tailored made AI tools useful to compare, integrate, and analyse in a secure, cost-effective fashion; with the very final aim of supporting the improvement of citizen’s health outcomes. In detail, this interdisciplinary project proposes the co-creation of 3 clinical use cases involving 7 medical centres located in the EU and beyond, where sensitive patient data, including genomics, are made available and analysed in a GDPR-compliant mechanism via a Distributed Analytics (DA) paradigm called the Personal Health Train (PHT). The main principle of the PHT is that the analytical task is brought to the data provider (medical centre) and the data instances remain in their original location. In this project, two mature implementations of the PHT (PADME and Vantage6) already validated in real-world scenarios will be fused together to build the BETTER platform.", journal = "European Comission, Horizon Europe", title = "Better real-world health-data distributed analytics research platform", url = "https://hdl.handle.net/21.15107/rcub_imagine_2307" }
(2024). Better real-world health-data distributed analytics research platform. in European Comission, Horizon Europe. https://hdl.handle.net/21.15107/rcub_imagine_2307
Better real-world health-data distributed analytics research platform. in European Comission, Horizon Europe. 2024;. https://hdl.handle.net/21.15107/rcub_imagine_2307 .
"Better real-world health-data distributed analytics research platform" in European Comission, Horizon Europe (2024), https://hdl.handle.net/21.15107/rcub_imagine_2307 .