For the study, they used artificial intelligence, which uses large amounts of data and complex algorithms to train the models. The team developed a model for detecting Alzheimer’s disease based on MRI data from patients with and without Alzheimer’s disease.
The group then tested the model on five datasets from different hospitals. Overall, 11,103 images from 2,348 patients at risk of developing Alzheimer’s disease and 26,892 images from 8,456 patients without Alzheimer’s disease participated in the study. The model determined Alzheimer’s disease risk with 90.2% accuracy across all five datasets.
Among the biggest innovations of the study is its ability to detect Alzheimer’s disease independently of other variables such as age.
Source: Ferra
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