This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 964220.

About AI-Mind research

The goal of the research is to reduce the disease’s burden by developing novel, AI-based tools to support healthcare professionals in their diagnosis and offering timely interventions to patients.

Besides time-consuming patient investigations with low discriminative power for dementia risk, current treatment options focus on late symptom management. What is now complex, labor-intensive, costly, and poorly predictive screening methods for mild cognitive impairment (MCI) shall be replaced by automated diagnostic screening tools. These are driven by artificial intelligence to address the urgent need for early accurate diagnosis and risk prediction.

AI-Mind will disrupt the clinical setting and significantly impact patients’ and doctors’ diagnostic journeys. Physicians will have a supportive decision-making tool that is able to identify patients at risk of developing dementia with high probability. 

AI-Mind enables earlier preventative therapies

With the currently available technology, many patients receive their diagnosis only after the onset of dementia. As a consequence, there might not be the opportunity to start preventive therapies. For people with mild cognitive impairment (MCI), the dementia risk is almost 30% higher than unaffected individuals. Therefore, we need effective diagnostic tools for early dementia risk assessment and intervention for people with MCI.  

Framweork

Activities in the AI-Mind are organised in nine integrated work packages (WP) cumulating in the delivery of a cloud-based platform containing AI tools that can quickly analyse data input. This work packages, often in parallel, complete tasks regarding:

  • concept governance and assessment of clinical landscape for tools implementation
  • data management and feature extraction
  • AI-modelling for the AI-Mind Connector and AI-Mind Predictor
  • Data analysis and visualisation platform for AI-Mind tools
  • clinical implementation and validation of AI-Mind Connector and AI-Mind Predictor
  • health technology assessment of AI-Mind tools
  • project outreach and exploitation of results
  • innovation management
  • ethic requirements
An innovative solution for early detection of dementia

Concept

At the heart of AI-Mind are two artificial intelligence based digital tools that will be integrated into a cloud-based diagnostic support platform. These tools will analyse existing and routinely collected data in an innovative manner: the AI-Mind Connector will fully automate the identification of early brain network disturbances; after enriching data from AI-Mind Connector with genetic and cognitive information, AI-Mind Predictor will provide an early marker of risk for dementia in people with MCI.

Our Ambition

The dementia patient journey at the moment involves several clinical visits, which finally result in a diagnosis of dementia two to five years after initial symptoms. AI-Mind  will shorten the time to diagnosis to a week and allow for diagnosis at the MCI stage, when there are no severe structural cerebral defects and intervention is still possible. AI-Mind will extend the ‘dementia-free’ period among MCI-patients who are prodromal to dementia by offering diagnosis and early intervention.

AI-Mind is an European project receiving funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 964220. It is a five-year Research and Innovation Action (RIA) that officially starts in March 2021. It involves fifteen project partners from eight European countries and has a budget around 14 million euro.

Horizon 2020 is the financial instrument implementing the Innovation Union, a Europe 2020 flagship initiative aimed at securing Europe's global competitiveness. This programme is followed by Horizon Europe, the new EU research and innovation programme for 2021-2027.

The AI-Mind project addresses the Horizon 2020 Call H2020-SC1-BHC-06-2020, ‘Digital diagnostics – developing tools for supporting clinical decisions by integrating various diagnostic data,’ by developing a decision support diagnostics platform for early risk estimation of dementia through two BSOA AI-based tools using SOA data.