Comprehensive solutions of healthcare improvement based on the global Registry of Stroke Care Quality

HORIZON.2.1HORIZON-RIAID: 101057603
EC Contribution
€77,027
Consortium Size
22 orgs
Summary

RES-Q+ will build on the success of RES-Q (REgistry of Stroke Care Quality) - currently, used by many EU countries and 74 worldwide - to improve stroke care quality by collecting and analyzing hospital discharge reports. RES-Q+ will revolutionize these improvements by capturing the whole patient pathway. The solution will combine NLP with a clinically-validated semantic model to automate ingestion of hospital discharge reports in different languages and assist with audit and feedback. This will include creating a standard model for such reports and using AI to impute missing data. Further augmentations include the creation of two novel AI voice assistants, one to help patients provide feedback on their health and the other to help physicians provide high quality care.We will integrate all these tools into RES-Q+. This will be the basis for a European Open Stroke Data Platform, an open research platform for data aggregation, semantic harmonization and interoperability across European countries to promote the use and re-use of health data. We will facilitate efforts to define a standard European Stroke Hospital Discharge Report Exchange Format as a tool for better secondary use of data and healthcare in general. Consortium legal partners will develop a comprehensive legal and ethical toolbox as guidance towards legal compliance. This will boost wider adoption of such novel AI-based solutions by integrating all current and proposed Union legislation. Our clinical partners will provide medical records and steer the development to maximize clinical utility and validate final solutions. RES-Q+ will be deployed globally to solidify our position as European and global leader in quality improvement. Eventually we will guarantee citizens a similar level of quality control during hospitalizations as when flying in a commercial plane.

Consortium (22)

Project Results (32)

Source: CORDIS, the EU research results database.

Publications (24)
<i>Stroke</i> Literature Synopsis (Clinical)
Stroke· 2025DOI
Kalliopi Mavromati, Terence J. Quinn
<i>Stroke</i> Literature Synopsis (Clinical)
Stroke· 2025DOI
Lucie Tvrdá, Terence J. Quinn
CUNI-a at ArchEHR-QA 2025: Do we need Giant LLMs for Clinical QA?
Proceedings of the 24th Workshop on Biomedical Language Processing (Shared Tasks)· 2025DOI
Pecina, Pavel; Lanz, Vojtěch
End-to-End Deep Learning for Named Entity Recognition and Relation Extraction in Gut-Brain Axis PubMed Abstracts
· 2025
Aleksis Ioannis Datseris, Mario Kuzmanov, Ivelina Nikolova-Koleva, Dimitar Taskov and Svetla Boytcheva
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence· 2025DOI
Francisco Abad-Navarro; Catalina Martínez-Costa; Jesualdo Tomás Fernández-Breis
Enigma @ ELCardioCC: Bridging NER and ICD-10 Entity
· 2025
Boris Velichkov, Aleksis Datseris, Sylvia Vassileva and Svetla Boytcheva
FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts
· 2025DOI
Sylvia Vassileva, Ivan K. Koychev and Svetla Boytcheva
Graphwise @ CLEF-2025 GutBrainIE: Towards Automated Discovery of Gut-Brain Interactions - Deep Learning for NER and Relation Extraction from PubMed Abstracts
· 2025
Aleksis Datseris, Mario Kuzmanov, Ivelina Nikolova-Koleva, Dimitar Taskov, Svetla Boytcheva
Semantic Representation of Medical Data Collection Forms Using Standards
Studies in Health Technology and Informatics, Intelligent Health Systems – From Technology to Data and Knowledge· 2025DOI
Stefan Schulz, Catalina Martínez Costa
SynthMedic: Utilizing large language models for synthetic discharge summary generation, correction and validation
Journal of Biomedical Informatics· 2025DOI
Georgi Grazhdanski, Vasil Vasilev, Sylvia Vassileva, Dimitar Taskov, Izabel Antova, Ivan Koychev, Svetla Boytcheva
Using LLMs for Multilingual Clinical Entity Linking to ICD-10
· 2025DOI
Sylvia Vassileva, Ivan K. Koychev and Svetla Boytcheva
When Multilingual Models Compete with Monolingual Domain-Specific Models in Clinical Question Answering
Proceedings of the Second Workshop on Patient-Oriented Language Processing (CL4Health)· 2025DOI
Pecina, Pavel; Lanz, Vojtěch
‘SNOMEDizing’ Questionnaires for Standardizing Stroke Registry Data
Studies in Health Technology and Informatics, Digital Health and Informatics Innovations for Sustainable Health Care Systems· 2024DOI
Andrea Riedel, Stefan Schulz, Catalina Martínez Costa
Comparing the properties of traditional and novel approaches to the modified Rankin scale: Systematic review and meta-analysis
European Stroke Journal· 2024DOI
Lucie Tvrda; Kalliopi Mavromati; Martin Taylor-Rowan; Terence J Quinn
Emotional design of medical devices: exoskeletons and post-stroke recovery devices
Proceedings of the Design Society· 2024DOI
Frederik Kiersgaard Lund, Luke Edward Eric Feast, Milo Marsfeldt Skovfoged, Hendrik Knoche, Mostafa Mohammadi, Lotte N. S. Andreasen Struijk, Linda Nhu Laursen
Focusing on what matters:Crafting stroke survivor personas relevant to systems supporting their self-management
Nemcova, V, Kunešová, V, Mikulik, R & Knoche, H 2024, Focusing on what matters : Crafting stroke survivor personas relevant to systems supporting their self-management. in NordiCHI '24 : Adjunct Proceedings of the 13th Nordic Conference on Human-Computer Interaction., 5, Association for Computing Machinery (ACM), NordiCHI 2024, Uppsala, Sweden, 13/10/2024. https://doi.org/10.1145/3677045.3685419· 2024DOI
Nemcova, Veronika; Kunešová, Veronika; Mikulik, Robert; Knoche, Hendrik
Paragraph Retrieval for Enhanced Question Answering in Clinical Documents
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing· 2024DOI
Vojtech Lanz, Pavel Pecina
Predictors of social risk for post-ischemic stroke reintegration
Scientific Reports· 2024DOI
Katryna K. Cisek, Thi Nguyet Que Nguyen, Alejandro Garcia-Rudolph, Joan Saurí, Helard Becerra Martinez, Andrew Hines, John D. Kelleher
Transformer-based approach for symptom recognition and multilingual linking
Database· 2024DOI
Sylvia Vassileva, Georgi Grazhdanski, Ivan Koychev, Svetla Boytcheva
Transformer-Based Disease and Drug Named Entity Recognition in Multilingual Clinical Texts: MultiCardioNER challenge
· 2024
"""Anna Aksenova, Aleksis Datseris, Sylvia Vassileva, Svetla Boytcheva"""
"""Feeling Unseen"":Exploring the Impact of Adaptive Social Robots on User’s Social Agency During Learning"
"Ziadeh, H, Ceccato, C, Prinsen, J, Pruss, E, Vrins, A, Knoche, H & Alimardani, M 2023, ""Feeling Unseen"" : Exploring the Impact of Adaptive Social Robots on User’s Social Agency During Learning. in Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction : HRI ’23 Companion. Association for Computing Machinery (ACM), pp. 378-383, ACM/IEEE International Conference on Human-Robot Interaction (HRI'23 WYSD Workshop), Stockholm, Sweden, 13/03/2023. https://doi.org/10.1145/3568294.3580110"· 2023DOI
Ziadeh, Hamzah; Ceccato, Caterina; Prinsen, Jos; Pruss, Ethel; Vrins, Anita; Knoche, Hendrik; Alimardani, Maryam
Feeling Unseen: Exploring the Impact of Adaptive Social Robots on User's Social Agency During Learning
Late-breaking reports in CHI'23· 2023DOI
Hamzah Ziadeh Caterina Cecatto Jos Prinsen Ethel Pruss Anita Vrins Hendrik Knoche Maryam Alimardani
Identifying Challenges and Opportunities for Intelligent Data-Driven Health Interfaces to Support Ongoing Care
Extended Abstracts of CHI'23· 2023DOI
Hendrik Knoche, Alfie Abdul-Rahman, Leigh Clark, Vasa Curcin, Zhiqiang Huo, Leonardo Horn Iwaya, Oliver Lemon, Robert Mikulik, Timothy Neate, Abi Roper, Milo M Skovfoged, Nervo Verdezoto, Stephanie Wilson, Hamzah Ziadeh
IEEE Access
IEEE Access· 2023DOI
Francisco Abad-Navarro; Catalina Martínez-Costa; Jesualdo Tomás Fernández-Breis
Deliverables (7)
Documents, reports
Documents, reports
Websites, patent fillings, videos etc.
Documents, reports
Websites, patent fillings, videos etc.
Other Results (1)
Periodic Reporting for period 1 - RES-Q PLUS (Comprehensive solutions of healthcare improvement based on the global Registry of Stroke Care Quality)