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A team of researchers at Massachusetts General Hospital have developed a method for accurately detecting signs of Alzheimer’s disease using routinely collected clinical brain imaging tests. The study, which is published in PLOS ONE, used deep learning – a type of machine learning and artificial intelligence – to develop a model for Alzheimer’s disease detection based on data from brain magnetic resonance images. The model was tested on two datasets and achieved an accuracy of up to 95%.
