AIDAVA: Difference between revisions

From Research Wiki
Newer edit →
Added/updated
 
Fixed references with proper URLs
Line 5: Line 5:


== Overview ==
== Overview ==
AIDAVA protypes 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>OpenAIRE / CORDIS (Grant 101057062): "AI powered Data Curation & Publishing Virtual Assistant"</ref>
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>


== Key Facts ==
== Key Facts ==
Line 12: Line 12:
! Detail !! Value
! Detail !! Value
|-
|-
| Grant ID || 101057062
| Grant ID || [https://cordis.europa.eu/project/id/101057062 101057062]
|-
|-
| Funding Call || HORIZON-HLTH-2021-TOOL-06
| Funding Call || HORIZON-HLTH-2021-TOOL-06
Line 34: Line 34:


== Vision ==
== Vision ==
"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.<ref>aidava.eu homepage</ref>
"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>


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.<ref>OpenAIRE project summary, 101057062</ref>
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>


== Technology Pillars ==
== Technology Pillars ==
# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
# '''Automation of quality enhancement and FAIRification''' of collected health data, in compliance with EU data privacy
# '''Knowledge graphs with ontology-based standards''' as universal representation, to increase interoperability and portability — 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.eu/about</ref>
# '''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>
# '''Deep learning for information extraction''' from narrative content (NLP in three languages)
# '''Deep learning for information extraction''' from narrative content — NLP developed in three languages
# '''AI-generated explanations''' during the process to increase users' confidence (explainability)
# '''AI-generated explanations''' during the process to increase users' confidence (explainability)<ref>AIDAVA, "Solution" — https://aidava.eu/about/solution</ref>


== Use Cases ==
== Use Cases ==
Line 48: Line 48:
# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time
# '''Longitudinal health records for cardiovascular patients''' — integrating heterogeneous data sources over time


Both tested in three languages with hospitals and emerging personal data intermediaries.<ref>OpenAIRE project summary</ref>
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>


== Solution Architecture ==
== Solution Architecture ==
Line 55: Line 55:
* '''Conversational AI assistant''' — engages patients, with explainability capabilities
* '''Conversational AI assistant''' — engages patients, with explainability capabilities
* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
* '''Metadata capture''' — on data sources to support automation within a formalised Data Transfer Specification
* Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging<ref>aidava.eu/about</ref>
* 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>


== Impact ==
== Impact ==
Line 62: Line 62:
* Support clinical research with reusable, interoperable data
* Support clinical research with reusable, interoperable data
* Long-term: democratise participation in data curation by citizens/patients
* Long-term: democratise participation in data curation by citizens/patients
* Support delivery of the European Health Data Space (EHDS)<ref>OpenAIRE project summary</ref>
* 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>


== Partners ==
== Partners ==
Line 73: Line 73:
| [[KU Leuven]] || Belgium || Research partner
| [[KU Leuven]] || Belgium || Research partner
|-
|-
| [[i-HD]] || Belgium || Health data standards & quality
| [[i-HD]] || Belgium || Health data standards and quality
|-
|-
| [[Egnosis]] || Romania || Health data intermediary
| [[Egnosis]] || Romania || Health data intermediary
Line 79: Line 79:
| [[Ontotext]] || Bulgaria || Knowledge graph technology
| [[Ontotext]] || Bulgaria || Knowledge graph technology
|-
|-
| [[Averbis]] || Germany || NLP / text mining
| [[Averbis]] || Germany || NLP and text mining
|-
|-
| [[Medical University of Graz]] || Austria || Clinical partner
| [[Medical University of Graz]] || Austria || Clinical partner
Line 95: Line 95:
| [[EURICE]] || Germany || Project management
| [[EURICE]] || Germany || Project management
|}
|}
All partners identified via OpenAIRE/CORDIS project registry.<ref>OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA</ref>


== Related Topics ==
== Related Topics ==
Line 102: Line 104:
* [[EU Regulation]]
* [[EU Regulation]]


== See Also ==
== External Links ==
* [https://aidava.eu Official AIDAVA website]
* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
* [https://cordis.europa.eu/project/id/101057062 CORDIS project page]
* [https://aidava.eu Official website]
* [https://doi.org/10.3030/101057062 DOI: 10.3030/101057062]


<references />
<references />
[[Category:Project]]
[[Category:Project]]
[[Category:EU]]
[[Category:EU]]

Revision as of 17:27, 13 April 2026

AIDAVA

AI-powered Data Curation & Publishing Virtual Assistant. EU Horizon Europe research project automating curation and publishing of personal health data using AI.

Overview

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.[1]

Key Facts

Detail Value
Grant ID 101057062
Funding Call HORIZON-HLTH-2021-TOOL-06
Total Cost €7,720,620
EU Contribution €7,720,620 (100% funded)
Start Date September 1, 2022
End Date August 31, 2026
Duration 4 years
Partners 13 from 9 countries
Type Horizon Europe Research and Innovation Action (RIA)
Website aidava.eu

Vision

"Curate once, reuse many times" — supporting patients, clinical care providers and clinical researchers from the same curated data.[2]

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.[3]

Technology Pillars

  1. Automation of quality enhancement and FAIRification of collected health data, in compliance with EU data privacy
  2. 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[4]
  3. Deep learning for information extraction from narrative content — NLP developed in three languages
  4. AI-generated explanations during the process to increase users' confidence (explainability)[5]

Use Cases

  1. Breast cancer patient registries — structured registry data curation
  2. Longitudinal health records for cardiovascular patients — integrating heterogeneous data sources over time

Both tested in three languages with hospitals and emerging personal data intermediaries.[6]

Solution Architecture

  • Data cleaning machine — orchestrating multiple AI-based tools to automate curation
  • Personal Health Knowledge Graph (PHKG) — universal semantic representation of all personal health data
  • Conversational AI assistant — engages patients, with explainability capabilities
  • Metadata capture — on data sources to support automation within a formalised Data Transfer Specification
  • Tools orchestrated include: OCR, syntactic transformation, semantic transformation, entity deduplication, NLP, feature extraction from imaging[7]

Impact

  • Decrease workload of clinical data stewards through increased automation
  • Improve effectiveness of clinical care through high-quality data
  • Support clinical research with reusable, interoperable data
  • Long-term: democratise participation in data curation by citizens/patients
  • Support delivery of the European Health Data Space (EHDS)[8]

Partners

Organization Country Role
Maastricht University Netherlands Coordinator
KU Leuven Belgium Research partner
i-HD Belgium Health data standards and quality
Egnosis Romania Health data intermediary
Ontotext Bulgaria Knowledge graph technology
Averbis Germany NLP and text mining
Medical University of Graz Austria Clinical partner
North Estonia Regional Hospital Estonia Clinical partner (use case)
European Cancer Patient Coalition Belgium Patient advocacy
European Heart Network Belgium Patient advocacy (cardiovascular)
B!LOBA Belgium Data management
DFP Research Spain Research partner
EURICE Germany Project management

All partners identified via OpenAIRE/CORDIS project registry.[9]

Related Topics

External Links

  1. ↑ European Commission CORDIS, Grant 101057062: "AI powered Data Curation & Publishing Virtual Assistant" — https://cordis.europa.eu/project/id/101057062
  2. ↑ AIDAVA official website — https://aidava.eu
  3. ↑ European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062
  4. ↑ AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts
  5. ↑ AIDAVA, "Solution" — https://aidava.eu/about/solution
  6. ↑ European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062
  7. ↑ AIDAVA, "Vision and Key Facts" — https://aidava.eu/about/vision-and-key-facts
  8. ↑ European Commission CORDIS, Grant 101057062, project summary — https://cordis.europa.eu/project/id/101057062
  9. ↑ OpenAIRE, AIDAVA project 101057062 — https://api.openaire.eu/search/projects?keywords=AIDAVA
Retrieved from "https://wiki.stamen.health/index.php?title=AIDAVA&oldid=105"