In a recent study published in Alzheimer’s & Dementia , researchers developed a method for predicting the progression of Alzheimer’s disease (AD). Study: Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models . Image Credit: fizkes/Shutterstock.
com Individuals with mild cognitive impairment (MCI) have a heightened risk of AD. Therefore, accurate prediction of the progression from MCI to AD can help in treatment-related decisions, selection for trials of new drugs, and participation in rehabilitation programs. AD pathology has been conventionally assessed using neuroimaging techniques or biomarkers.
Various studies have evaluated these (conventional) methods for predicting MCI to AD progression. However, they are expensive and invasive, limiting their applicability. By contrast, neuropsychological tests (NPTs) are the most accessible for cognitive decline assessment.
Computer-based approaches have been tested for predicting MCI-to-AD conversion using NPTs. Speech in NPTs can be used to predict cognitive decline. Artificial intelligence-based diagnostic models using acoustic and linguistic features from NPTs have been developed.
The Framingham Heart Study (FHS) has been recording NPTs since 2005, and the recordings have been used to build diagnostic tools. Previously, the study’s authors applied natural language processing (NLP) techniques on recordings to place individuals across the dementia spectrum. In th.
