New Delhi: Researchers in China have developed an innovative voice-based approach to facilitate the early detection of Alzheimer’s disease.
The study, led by Prof. Li Hai at the Hefei Institutes of Physical Science, Chinese Academy of Sciences, highlights the growing prevalence of Alzheimer’s due to an aging global population. The researchers emphasized that early diagnosis is essential for improving patient care and treatment outcomes.
“Language deterioration is often one of the earliest indicators of cognitive decline,” the team stated in their study, published in the IEEE Journal of Biomedical and Health Informatics.
While existing speech-based diagnostic tools offer a non-invasive and cost-effective method for Alzheimer’s detection, they are often hindered by complexity, limited data integration, and poor interpretability, which reduces their reliability in clinical settings.
To address these challenges, Hai’s team developed DEMENTIA, a novel framework that enhances diagnostic accuracy and clinical usability.
“This innovative model combines speech, text, and expert insights through a hybrid attention mechanism, significantly improving the precision and interpretability of Alzheimer’s detection,” the researchers explained.
The framework leverages large language models and captures complex interactions within speech data, enabling more accurate predictions of cognitive function scores. Moreover, it demonstrates strong decision-support capabilities, making it adaptable across diverse datasets and clinical scenarios.
The study underscores the potential of voice-based tools in early Alzheimer’s screening and monitoring cognitive decline, offering a promising solution for timely diagnosis and intervention.
Alzheimer’s is a progressive neurodegenerative disorder that affects memory and cognitive function, accounting for around 75% of dementia cases worldwide. Of the 55 million people living with dementia globally, an estimated 60–70% have Alzheimer’s.
By refining early detection methods, the AI-powered voice analysis framework could revolutionize Alzheimer’s diagnosis, making it more accessible, interpretable, and clinically relevant. The integration of AI in healthcare continues to show promise in addressing major medical challenges, paving the way for more effective disease management and intervention strategies.