What is it about?

This study aimed to determine whether the unsupervised discovering subtypes of subjects with Mild Cognitive Impairment (MCI) could be useful in finding different prodromal Alzheimer's Disease stages. We took advantage of consensus data clustering to identify these subtypes. Our findings revealed three different subtypes of patients with MCI at early stage. At-risk groups showed a different trajectory than the low-risk subtype.

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Why is it important?

The ability to correctly predict the diagnosis of Alzheimer’s disease in its earliest stages can help physicians make more informed clinical decisions on therapy plans.

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This page is a summary of: Robust Discovery of Mild Cognitive Impairment Subtypes and Their Risk of Alzheimer's Disease Conversion Using Unsupervised Machine Learning and Gaussian Mixture Modeling, Current Alzheimer Research, November 2021, Bentham Science Publishers, DOI: 10.2174/1567205018666210831145825.
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