Researchers from the University of Cambridge’s Department of Psychology have developed a new AI model that outperforms current clinical tests in predicting the progression of Alzheimer’s disease.
The machine learning model accurately predicts Alzheimer’s disease progression in four out of five cases using non-invasive data.
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Published in eClinical Medicine, it utilises cognitive tests and MRI scans to forecast whether individuals with mild cognitive impairment will develop Alzheimer’s.
This could lead to earlier interventions and reduce the reliance on costly diagnostic procedures.
The AI model was crafted using data from more than 400 individuals and validated with patient data from 600 participants in the US and 900 from memory clinics in Singapore and the UK.
It was able to identify those who would develop Alzheimer’s within three years with an 82% accuracy rate, and those who would not with an 81% accuracy rate, solely from cognitive tests and MRI scans.
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By GlobalDataThe model enables the stratification of Alzheimer’s patients into three categories based on the predicted rate of disease progression, validated by six years of follow-up data.
The algorithm’s robustness was confirmed using independent data from nearly 900 individuals from memory clinics, demonstrating its applicability in real-world clinical settings.
University of Cambridge Department of Psychology senior author professor Zoe Kourtzi said: “We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow.
“This has the potential to significantly improve patient well-being, showing us which people need closest care, while removing the anxiety for those patients we predict will remain stable.”
Looking ahead, the research team aims to expand the model’s application to other forms of dementia and incorporate additional types of data, such as blood test markers.
This research received support from various institutions, including Wellcome, Alzheimer’s Research UK, the Royal Society, and the National Institute for Health and Care Research Cambridge Biomedical Research Centre.
