HELSINKI (Dispatches)- A machine learning method analyzing large amounts of health information has potential in assessing the risk of cognitively healthy older people for later dementia, according to research.
Recent developments in dementia prevention research include large online Brain Health Registries, multinational data discovery and sharing platforms, and internet-based prevention trials. Dealing with large amounts of health information -- "big data"- is a challenging consequence of these developments. Machine learning represents a type of artificial intelligence where a group of methods is used to teach computers to make and improve predictions based on large datasets. These methods are just starting to be used in the context of dementia prevention.
A team of medical doctors and engineers from Finland and Sweden addressed these challenges using a novel machine learning approach. They developed a dementia risk index -- a tool for assessing people's risk of dementia and for indicating the most relevant target areas for preventive measures. An added advantage of the tool is the ability to show detailed individual dementia risk profiles in a visual format that is easy to interpret.
Risk index predicted dementia ten years before onset.
The researchers conclude that the risk index could be useful for identifying older individuals who are most at risk, and who may also benefit most from preventive interventions. They emphasize that the risk index is not meant for dementia diagnosis, but as a tool to help with making decisions about dementia prevention strategies, i.e. to whom these should be targeted, and what risk factors should be specifically addressed based on the visual risk profile.