Speech acoustics effectively capture the risk of preclinical Alzheimer's disease as defined by p-tau217 and APOE status.
The study demonstrates a link between spontaneous speech patterns and underlying Alzheimer's biomarkers, offering a new detection strategy.
Utilizing advanced methodologies for analyzing speech, the research highlights this novel approach to risk evaluation.
The findings support the potential for speech-based assessments, emphasizing the need for broader applications in clinical settings.
Abstract
Spontaneous speech acoustics capture p-tau217/APOE-defined AD risk despite preserved cognition, supporting speech as a scalable, biologically grounded biomarker for preclinical AD risk stratification.