A new case of dementia is diagnosed somewhere in the world every three seconds. Research shows as many as 40 percent of cases could be prevented or delayed, but doing so requires collecting and analysing vast amounts of data. Artificial Intelligence (AI) can support clinicians in diagnosing and predicting dementia with up to 90 percent accuracy, though care is needed to manage the ethical issues surrounding patient privacy, data security and the introduction of human bias.
Although the cause and risk factors for 60 percent of dementia cases remain unknown, a recent study has identified that 12 modifiable risk factors together account for about 40 percent of dementia cases worldwide. Earlier identification of these recognised risks and efforts to determine those which are still not known could pave the way for the prevention and improved care of dementia.
The potential benefits of AI, including reducing the risks of dementia by analysing vast amounts of health data and offering patient-tailored recommendations, are substantial. Machine learning — a division of AI that automates analysis and computations by learning from data to identify patterns — can analyse large sets of patient information to detect patterns of dementia warning signs with minimal (or without) human involvement. These include subtle signs such as difficulties in thinking and understanding daily tasks, emotional lability and memory loss which could otherwise be missed by clinicians.
