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| __NOTOC__
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| AI-powered Data Curation & Publishing Virtual Assistant. EU Horizon Europe research project automating curation and publishing of personal health data using AI.
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| == Overview ==
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| AIDAVA prototypes and tests an AI-powered virtual assistant that maximizes automation of data curation and publishing of unstructured and structured, heterogeneous health data. The assistant includes a backend library of AI-based data curation tools and a frontend based on human-AI interaction modules.<ref>European Commission CORDIS, Grant 101057062: "AI powered Data Curation & Publishing Virtual Assistant" — https://cordis.europa.eu/project/id/101057062</ref>
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| == Key Facts ==
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| {|
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| ! Detail !! Value
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| | Grant ID || [https://cordis.europa.eu/project/id/101057062 101057062]
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| | Funding Call || HORIZON-HLTH-2021-TOOL-06
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| | Total Cost || €7,720,620
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| | EU Contribution || €7,720,620 (100% funded)
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| | Start Date || September 1, 2022
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| | End Date || August 31, 2026
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| | Duration || 4 years
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| | Partners || 13 from 9 countries
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| | Type || Horizon Europe Research and Innovation Action (RIA)
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| | Website || [https://aidava.eu aidava.eu]
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| |}
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| == Vision ==
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| "Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>AIDAVA official website — https://aidava.eu</ref>
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| The project addresses the core problem that integrated, high-quality personal health data represents a potential wealth of knowledge for healthcare systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale across institutions, at national and EU level.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>
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| == Technology Pillars ==
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| # '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
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| # '''Knowledge graphs with ontology-based standards''' as universal representation — each Personal Health Knowledge Graph (PHKG) is an instance of a common reference knowledge graph based on ontologies derived from SNOMED, HL7 FHIR resource profiles, LOINC, and other domain-specific terminologies<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>
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| # '''Deep learning for information extraction''' from narrative content — NLP developed in three languages
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| # '''AI-generated explanations''' during the process to increase users' confidence (explainability)<ref>AIDAVA, "Solution" — https://aidava.eu/about/solution</ref>
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| == Use Cases ==
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| # '''Breast cancer patient registries''' — structured registry data curation
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| # '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time
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| Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>
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| == Solution Architecture ==
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| * '''Data cleaning machine''' — orchestrating multiple AI-based tools to automate curation
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| * '''Personal Health Knowledge Graph (PHKG)''' — universal semantic representation of all personal health data
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| * '''Conversational AI assistant''' — engages patients, with explainability capabilities
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| * '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
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| * Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts</ref>
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| == Impact ==
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| * Decrease workload of clinical data stewards through increased automation
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| * Improve effectiveness of clinical care through high-quality data
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| * Support clinical research with reusable, interoperable data
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| * Long-term: democratise participation in data curation by citizens/patients
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| * Support delivery of the European Health Data Space (EHDS)<ref>European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062</ref>
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| == Partners ==
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| {| class="wikitable"
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| ! Organization !! Country !! Role
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| | [[Maastricht University]] || Netherlands || Coordinator
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| | [[KU Leuven]] || Belgium || Research partner
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| | [[i-HD]] || Belgium || Health data standards and quality
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| | [[Egnosis]] || Romania || Health data intermediary
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| | [[Ontotext]] || Bulgaria || Knowledge graph technology
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| | [[Averbis]] || Germany || NLP and text mining
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| | [[Medical University of Graz]] || Austria || Clinical partner
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| | [[North Estonia Regional Hospital]] || Estonia || Clinical partner (use case)
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| | [[European Cancer Patient Coalition]] || Belgium || Patient advocacy
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| | [[European Heart Network]] || Belgium || Patient advocacy (cardiovascular)
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| | [[B!LOBA]] || Belgium || Data management
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| | [[DFP Research]] || Spain || Research partner
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| | [[EURICE]] || Germany || Project management
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| |}
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| All partners identified via OpenAIRE/CORDIS project registry.<ref>OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA</ref>
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| == Related Topics ==
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| * [[Knowledge Graphs in Health]]
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| * [[Interoperability]]
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| * [[Longitudinal Journals]]
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| * [[EU Regulation]]
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| == External Links ==
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| * [https://aidava.eu Official AIDAVA website]
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| * [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
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| * [https://doi.org/10.3030/101057062 DOI: 10.3030/101057062]
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| <references />
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| [[Category:Project]]
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| [[Category:EU]]
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