Artificial intelligence opens a new path to diagnosing dementia and enhancing opportunities for early intervention

European researchers are turning to using artificial intelligence to develop tools that help diagnose dementia early, by identifying people most at risk of developing cognitive decline before the condition reaches advanced stages.

These efforts come at a time when dementia affects about 57 million people around the world, while many cases are not discovered until important changes occur in the brain, which may reduce the chances of early intervention and obtaining appropriate support.

AI-Mind project, funded by the European Union, works on using brain electrical activity data and informationMedical and biomarkers to assess the risk of mild cognitive impairment developing into dementia, emphasizing that the new tools are intended to support clinicians and not replace human medical decision-making.

Dementia begins before diagnosis

Researchers involved in the project say that reaching a diagnosis of dementia can take a long time, and in some cases patients and caregivers do not get the answers and support they need until after cognitive decline has progressed.

This problem becomes more important as the population ages, as project data indicate that dementia affects about 7% of those over the age of sixty in European Union countries.

Researchers are therefore focusing on a stage that precedes full-blown dementia, known as Mild cognitive impairment Mild Cognitive Impairment (MCI), a condition in which a person may suffer from problems with memory or performing some daily tasks, without all cases later developing into dementia.

The challenge is to identify people who are at high risk of developing the condition, so that they can be followed up more closely and offered support earlier.

Artificial intelligence looks for danger early

The AI-Mind team collected data from 1,000 European people, spending more than 50,000 hours collecting and analyzing it using custom systems to protect the privacy of participants’ information.

This data aims to train models capable of identifying patterns that may be associated with an increased risk of developing dementia, instead of waiting until symptoms appear.Clearer.

The researchers believe that improving risk assessment can expand opportunities for follow-up, intervention and support, and help patients and their families understand what is happening at an early stage.

This does not mean that artificial intelligence provides a diagnosis of dementia independently. Rather, it acts as a tool to analyze a wide range of indicators and help doctors evaluate the likelihood of developing the condition.

Two tools to analyze dementia risk

The project developed two integrated tools, the first of which is called AI-Mind Connector, and relies on electrical activity data of the brain to monitor patterns that may be associated with an increased risk of dementia.

The research on which the project was based indicates that some changes in the electrical activity of the brain may appear early during the development of the condition, which gives researchers an opportunityTo use this data in risk assessment.

The second tool, AI-Mind Predictor, uses artificial intelligence to analyze a broader set of data, including the results of the first tool, cognitive functions, vital signs, and medical history.

Factors such as age, education, and place of residence are also included in the analysis, with the aim of building a more comprehensive picture of a person’s odds of moving from mild cognitive impairment to dementia.

To learn about another application of artificial intelligence in supporting diagnosis and health care, read also: A new discovery… Artificial intelligence saves human lives .

Early detection expands opportunities for intervention

There is currently no cure for dementia, but some risk factors can be modified.This makes it more important to identify those most at risk of infection at an early stage.

Researchers point to factors such as social isolation, excessive alcohol consumption, and smoking, where lifestyle changes can be made that may help reduce some risks.

Early recognition of the possibility of developing dementia can also give people and their families a greater opportunity to plan for the future and obtain appropriate support before the condition progresses.

This trend intersects with the third goal of the Sustainable Development Goals (SDGs) on good health and well-being, especially with a focus on improving prevention and early detection and expanding access to appropriate care.

Researchers also believe that the emergence of new treatments in the coming years may increase the value of risk assessment tools, by helping to identify patients who couldThey benefit more from it.

The road to hospitals is still long

AI-Mind tools have already been tested in research and clinical environments in Norway, and the first phase of the project ended in early 2026, while the team is currently searching for funding that would allow it to continue the work and expand to other countries.

Before these tools can be used on a widespread medical scale, they need to obtain certification as medical devices under European Union rules, which requires a clinical evaluation that researchers expect to complete by 2035.

The team also plans to test the algorithms in more diverse settings and populations to ensure they can provide reliable results beyond the original participants.

The project also cooperates withIndustry players including Eli Lilly, Roche and Bosch are working to significantly advance the diagnostic approach.

This path intersects with the ninth goal of the Sustainable Development Goals (SDGs) on industry, innovation and infrastructure, especially with the development of new digital tools that can support health care services in the future.

For its part, The Earth Guards Foundation indicates that employing artificial intelligence in diagnosing dementia may open new opportunities to detect risks at earlier stages, while the medical decision remains based on human evaluation and direct interaction between the patient and healthcare professionals.