AI-based long-term health risk evaluation for driving behaviour change strategies in children and youth

Informacje na temat projektu

SmartCHANGE

Identyfikator umowy o grant: 101080965

DOI

10.3030/101080965

Data podpisania przez KE 20 Marca 2023

Data rozpoczęcia 1 Maja 2023

Data zakończenia 30 Kwietnia 2027

Finansowanie w ramach

• Health

Koszt całkowity

€ 5 967 395,00

Wkład UE

€ 5 967 395,00

Koordynowany przez

INSTITUT JOZEF STEFAN
Slovenia

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Rezultaty

Data Management Plan (1)

Data management plan

Best practices and standards for project data, assessment of suitability for sharing

Documents, reports (3)

Initial dissemination, communication and exploitation plan

Plan for dissemination, communication and exploitation, including stakeholder groups and targeted engagement activities

SELP benchmark

A description of key ethical and legal requirements, and their frame

Initial technical specification

Initial specification of the design of the system architecture integrating all the components defined in the project to be used in the pilot study

Websites, patent fillings, videos etc. (1)

Project website

Website with project presentation, news and public materials (website and a short description)

Publikacje

Other (2)

AI in Healthcare: The AI Act and other Regulatory Issues

Autorzy: Favaro, John
DOI: 10.5281/ZENODO.13935246

SmartCHANGE Webinar - Putting Health Tools into practice: Designing feasibility studies at an international scale

Autorzy: Domenici, Diego Dylan; op den Akker, Harm; Di Giacomo, Valentina; Jurak, Gregor; Tammelin, Tuija; Laaksonen, Heikki; Dictus, Claudia; Hoogsteder, Mariëtte; Ribeiro, Jose; Bomrah, Sherali
Opublikowane w: 2025
Wydawca: Zenodo
DOI: 10.5281/ZENODO.17581364

Conference proceedings (19)

AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model

Autorzy: Dominici, G.; Barbiero, P.; Giannini, Francesco; Gjoreski, M.; Langeinrich, M.
Opublikowane w: CoRR, 2024, ISSN 1613-0073
Wydawca: Cornell University -Arxiv
DOI: 10.48550/ARXIV.2405.16508

FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts

Autorzy: Dario Fenoglio, Mohan Li, Pietro Barbiero, Nicholas D. Lane, Marc Langheinrich, Martin Gjoreski
Opublikowane w: NeurIPS 2025, 2025
Wydawca: Cornell Univeristy - Arxiv
DOI: 10.48550/ARXIV.2511.22305

AnyCBMs How to Turn Any Black Box into a Concept Bottleneck Model

DOI: 10.5281/ZENODO.14582114

Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning

Autorzy: Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda, Martin Gjoreski, Marc Langheinrich
Opublikowane w: 2024
Wydawca: Cornell University - Arxiv
DOI: 10.48550/ARXIV.2405.15632

Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors

Autorzy: Dario Fenoglio; Mohan Li; Davide Casnici; Matías Laporte; Shkurta Gashi; Silvia Santini; Martin Gjoreski; Marc Langheinrich
Opublikowane w: 2024 International Conference on Intelligent Environments (IE), 2024, ISSN 2469-8792
Wydawca: IEEE
DOI: 10.48550/ARXIV.2512.03287

Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors

Autorzy: Dario Fenoglio, Mohan Li, Davide Casnici, Matias Laporte, Shkurta Gashi, Silvia Santini, Martin Gjoreski, Marc Langheinrich
Opublikowane w: 2024 International Conference on Intelligent Environments (IE), 2024
Wydawca: IEEE
DOI: 10.1109/IE61493.2024.10599924

Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning

Autorzy: Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich
Opublikowane w: ICLR 2025, 2025
Wydawca: Cornell University - Arxiv
DOI: 10.48550/ARXIV.2402.01408

Federated Learning for Privacy-aware Cognitive Workload Estimation

DOI: 10.1145/3626705.3627783

Health Risk Prediction for Children Built on a Combination of Heterogeneous Datasets

Autorzy: Kramar Sebastjan, Jordan Marko, Založnik Marcel, Reščič Nina, Luštrek Mitja
Opublikowane w: 2024, ISSN 2545-4990
Wydawca: Zenodo
DOI: 10.5281/ZENODO.14549545

SmartCHANGE Risk Prediction Tool: Next-Generation RiskAssessment for Children and Youth

Opublikowane w: IS 2025 - Slovenian Conference on Artificial Intellignece, 2025
Wydawca: Jozef Stefan Institute
DOI: 10.70314/IS.2025.SKUI.7226

A Data Modeling Process for Achieving Interoperability

Autorzy: Eleftheria Kouremenou, Athanasios Kiourtis, Dimosthenis Kyriazis
Opublikowane w: 2024
Wydawca: Springer Nature
DOI: 10.5281/ZENODO.14541883

A Cross-Sector Data Space for Correlating Environmental Risks with Human Health

Autorzy: Athanasios Kiourtis, Argyro Mavrogiorgou, Dimosthenis Kyriazis
Wydawca: Springer Nature
DOI: 10.5281/ZENODO.14541845

A Federated Unsupervised Personalisation for Cognitive Workload Estimation

Autorzy: Dario Fenoglio, Martin Gjoreski, Marc Langheinrich
Opublikowane w: Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, 2023
Wydawca: ACM
DOI: 10.1145/3626705.3631796

SmartCHANGE: AI-based long-term health risk evaluation for driving behaviour change strategies in children and youth

Autorzy: Nina Reščič, Janna Alberts, Teatske M. Altenburg, Mai J. M. Chinapaw, Antonio De Nigro, Dario Fenoglio, Martin Gjoreski, Anton Gradišek, Gregor Jurak, Athanasios Kiourtis, Dimosthenis Kyriazis, Marc Langheinrich, Elena Mancuso, Argyro Mavrogiorgou, Mykola Pechenizkiy, Roberto Pratola, José Ribeiro, Maroje Sorić, Fawad Taj, Tuija H. Tammelin, Martijn Vastenburg, Anna Vilanova, Tanja G. M. Vrijkotte, Mitja Luštrek
Opublikowane w: 2023 International Conference on Applied Mathematics & Computer Science (ICAMCS), 2024
Wydawca: IEEE
DOI: 10.1109/ICAMCS59110.2023.00020

SmartCHANGE Risk Prediction Tool: Demonstrating Risk Assessment for Children and Youth

Opublikowane w: Proceedings of Slovenian Conference on Artificial Intelligence 2024, 2024
Wydawca: Jožef Stefan Instutute
DOI: 10.70314/is.2024.scai.8844

Addressing Complex Data Integration and Harmonization Scenarios

Autorzy: University of Piraeus Research Center
Opublikowane w: 2024
Wydawca: Springer Nature
DOI: 10.5281/ZENODO.14541905

Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms andPredictive Bias

Autorzy: Adam Dubowski, Hilde Weerts, Anouk Wolters, Mykola Pechenizkiy
Opublikowane w: Lecture Notes in Computer Science, Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-70371-3_31

Counterfactual Concept Bottleneck Models

Autorzy: Dominici, G.; Barbiero, P.; Giannini, Francesco; Gjoreski, M.; Marra, G.; Langheinrich, M.
Opublikowane w: 2024
Wydawca: Cornell University - Arxiv
DOI: 10.48550/ARXIV.2402.01408

A Data Modeling Process for Achieving Interoperability

Autorzy: Eleftheria Kouremenou, Athanasios Kiourtis, Dimosthenis Kyriazis
Wydawca: Springer Nature
DOI: 10.5281/ZENODO.14541883

Peer reviewed articles (2)

Navigating multi-country, multi-disciplinary co-design with families, adolescents and healthcare practitioners: the SmartCHANGE project.

Autorzy: Claudia Dictus; Mai J.M. Chinapaw; Teatske M. Altenburg
Opublikowane w: Open Research Europe, 2025, ISSN 2732-5121
Wydawca: Open Research Europe
DOI: 10.12688/OPENRESEUROPE.21004.1

Prospective association between descriptive accelerometer-derived physical behaviour metrics and cardiometabolic risk indicators in Dutch children: The ABCD study

Autorzy: Fawad Taj, J.M.M. Chinapaw, Teatske Altenburg, Tanja Vrijkotte
Opublikowane w: Journal of Exercise Science & Fitness, Numer 24, 2026, ISSN 1728-869X
Wydawca: Elsevier BV
DOI: 10.1016/J.JESF.2025.200431