Periodic Reporting for period 3 - AI-Mind (Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment.)
Periodo di rendicontazione: 2023-09-01 al 2025-02-28
Every three seconds, someone in the world develops dementia. There are more than 100 million people worldwide living with mild cognitive impairment, and by 2030, this number is expected to nearly double, with 50% of those individuals expected to develop dementia. Current treatment options primarily focus on managing established symptoms, alongside time-consuming patient investigations that have limited effectiveness in determining dementia risk. The EU-funded AI-Mind project aims to address these challenges by screening brain connectivity and estimating dementia risk in individuals with mild cognitive impairment. Through the development of two artificial intelligence-based digital tools, the project seeks to identify dysfunctional brain networks and assess individual dementia risk. This innovation will enable the extension of the "dementia-free" period by facilitating early intervention and accurate diagnosis.
Significant progress has been made during the project's third reporting period. A key milestone was the successful finalisation of participant enrollment, reaching the clinical study target of over 1,000 individuals with mild cognitive impairment (MCI). This was achieved despite recruitment challenges at one site, which were effectively mitigated by reallocating recruitment efforts to other countries. The completion of the AI-Mind central database—hosted on the secure Services for Sensitive Data (TSD) platform at the University of Oslo—is well underway and near finalisation. This database integrates multimodal data from all clinical partners. Significant work has also gone into the harmonisation, standardisation, and BIDS-format storage of this data, ensuring its readiness for machine learning and clinical validation tasks.
The project has continued its close engagement with stakeholders, including clinical partners, industry representatives, and end users, through co-creation workshops and participatory design. This has guided the development of the AI-Mind Connector and Predictor tools—two AI-powered systems for early risk detection of dementia. While preliminary versions have been tested on subsets of data, the finalisation and full deployment of these tools is expected in the next period. Additionally, the project has developed a suite of educational and training materials to support end-user understanding and clinical adoption. A dedicated knowledge-sharing hub has been established on the AI-Mind website to host these resources and facilitate stakeholder engagement.
Notably, AI-Mind has carried out extensive dissemination and communication activities across multiple channels. These include participation in major international conferences, publications in peer-reviewed journals, social media outreach, and a high-visibility presence national medias. AI-Mind has also played a key role in fostering collaboration across European research project, becoming a partner in the newly funded EU-project FluiDx-AD.
Several scientific publications have been submitted during this period, including studies on functional connectivity metrics, validation of AI models, explainability in AI-supported diagnostics, and the development of ethical guidelines for trustworthy AI in clinical contexts.
Progress in innovation and exploitation has also been notable. The AI-Mind tools are being refined in accordance with the regulatory requirements for medical device software under the EU MDR. The decision-analytical model developed in WP6 for health technology assessment (HTA) has already been adopted in other EU-funded projects, demonstrating AI-Mind's broader value. Intellectual property assessments have been carried out, and discussions are ongoing with industrial partners on post-project commercialisation pathways.
In close collaboration with its industrial partners, the project continues to advance toward a groundbreaking clinical breakthrough—enabling scalable, AI-supported screening tools that can predict dementia risk in MCI patients before irreversible cognitive decline sets in. With all core components under development or in testing, AI-Mind is well-positioned for clinical implementation and real-world impact by the end of the project.
The project has continued its close engagement with stakeholders, including clinical partners, industry representatives, and end users, through co-creation workshops and participatory design. This has guided the development of the AI-Mind Connector and Predictor tools—two AI-powered systems for early risk detection of dementia. While preliminary versions have been tested on subsets of data, the finalisation and full deployment of these tools is expected in the next period. Additionally, the project has developed a suite of educational and training materials to support end-user understanding and clinical adoption. A dedicated knowledge-sharing hub has been established on the AI-Mind website to host these resources and facilitate stakeholder engagement.
Notably, AI-Mind has carried out extensive dissemination and communication activities across multiple channels. These include participation in major international conferences, publications in peer-reviewed journals, social media outreach, and a high-visibility presence national medias. AI-Mind has also played a key role in fostering collaboration across European research project, becoming a partner in the newly funded EU-project FluiDx-AD.
Several scientific publications have been submitted during this period, including studies on functional connectivity metrics, validation of AI models, explainability in AI-supported diagnostics, and the development of ethical guidelines for trustworthy AI in clinical contexts.
Progress in innovation and exploitation has also been notable. The AI-Mind tools are being refined in accordance with the regulatory requirements for medical device software under the EU MDR. The decision-analytical model developed in WP6 for health technology assessment (HTA) has already been adopted in other EU-funded projects, demonstrating AI-Mind's broader value. Intellectual property assessments have been carried out, and discussions are ongoing with industrial partners on post-project commercialisation pathways.
In close collaboration with its industrial partners, the project continues to advance toward a groundbreaking clinical breakthrough—enabling scalable, AI-supported screening tools that can predict dementia risk in MCI patients before irreversible cognitive decline sets in. With all core components under development or in testing, AI-Mind is well-positioned for clinical implementation and real-world impact by the end of the project.
AI-Mind has advanced beyond the state of the art by integrating multimodal neurophysiological, cognitive, genetic, and clinical data into a standardized, GDPR-compliant infrastructure for dementia risk prediction. The development of the AI-Mind Connector and Predictor tools marks a major step forward in non-invasive, explainable AI-based decision support, shifting diagnostics from invasive methods toward accessible and scalable screening in clinical practice.
A major achievement is the deployment of the project’s infrastructure on the Services for Sensitive Data (TSD) platform, which ensures secure and compliant handling of clinical data. AI-Mind has also aligned with European initiatives such as eBRAINS Health, facilitating cross-project collaboration and long-term data reuse beyond the project timeline. This connection enables continued innovation in functional connectivity analysis, explainable AI, and ethical implementation of AI in healthcare.
Strong collaboration with industrial partners has exceeded expectations, driven by AI-Mind’s adherence to high data quality and interoperability standards. These efforts are paving the way for the clinical translation of the tools, with potential pathways toward medical device certification.
By project end, AI-Mind will deliver validated diagnostic tools, a harmonized European brain health database, and clinical best practice guidelines for ethical and legal integration. These outcomes are intended to support healthcare professionals, inform national screening strategies, and enable earlier interventions to delay or prevent dementia onset.
The societal and economic impacts are considerable. With the rise in dementia costs in Europe, the AI-Mind’s tools have the potential to reduce long-term care costs, lessen caregiver burden, and improve quality of life by identifying at-risk individuals earlier. Furthermore, by strengthening collaboration between public institutions, academia, and industry, the project contributes to a sustainable and trustworthy European AI ecosystem for health innovation.
A major achievement is the deployment of the project’s infrastructure on the Services for Sensitive Data (TSD) platform, which ensures secure and compliant handling of clinical data. AI-Mind has also aligned with European initiatives such as eBRAINS Health, facilitating cross-project collaboration and long-term data reuse beyond the project timeline. This connection enables continued innovation in functional connectivity analysis, explainable AI, and ethical implementation of AI in healthcare.
Strong collaboration with industrial partners has exceeded expectations, driven by AI-Mind’s adherence to high data quality and interoperability standards. These efforts are paving the way for the clinical translation of the tools, with potential pathways toward medical device certification.
By project end, AI-Mind will deliver validated diagnostic tools, a harmonized European brain health database, and clinical best practice guidelines for ethical and legal integration. These outcomes are intended to support healthcare professionals, inform national screening strategies, and enable earlier interventions to delay or prevent dementia onset.
The societal and economic impacts are considerable. With the rise in dementia costs in Europe, the AI-Mind’s tools have the potential to reduce long-term care costs, lessen caregiver burden, and improve quality of life by identifying at-risk individuals earlier. Furthermore, by strengthening collaboration between public institutions, academia, and industry, the project contributes to a sustainable and trustworthy European AI ecosystem for health innovation.