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arXiv · 2104.14073

Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directions

Renjie Li·Xinyi Wang·Katherine Lawler·Saurabh Garg·Quan Bai·Jane Alty
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Abstract

With populations ageing, the number of people with dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases are due to Alzheimer's disease (AD) pathology and there is a 10-20 year 'pre-clinical' period before significant cognitive decline occurs. We urgently need, cost effective, objective methods to detect AD, and other dementias, at an early stage. Risk factor modification could prevent 40% of cases and drug trials would have greater chances of success if participants are recruited at an earlier stage. Currently, detection of dementia is largely by pen and paper cognitive tests but these are time consuming and insensitive to pre-clinical phases. Specialist brain scans and body fluid biomarkers can detect the earliest stages of dementia but are too invasive or expensive for widespread use. With the advancement of technology, Artificial Intelligence (AI) shows promising results in assisting with detection of early-stage dementia. Existing AI-aided methods and potential future research directions are reviewed and discussed.

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Renjie Li, Xinyi Wang, Katherine Lawler, Saurabh Garg, Quan Bai, Jane Alty. 2021-04-29. Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directions. https://arxiv.org/abs/2104.14073

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