Speech Patterns May Signal Future Alzheimer’s
Researchers from Boston University have developed a promising new AI algorithm that analyzes speech patterns to predict the progression from mild cognitive impairment (MCI) to Alzheimer’s disease. This approach could revolutionize early detection and intervention for Alzheimer’s, offering hope in managing the disease more effectively.
Detection of Alzheimer’s Through Speech Patterns
Nevertheless, despite not fully understanding the causes of Alzheimer’s, scientists are adept at recognizing its effects and are becoming increasingly proficient at detecting early signs. Among these early indicators might be subtle changes in the way people speak.
The Boston University team has created an AI algorithm that examines the speech of individuals with MCI. Impressively, “this tool can predict the likelihood of these individuals progressing to Alzheimer’s within six years, achieving an accuracy rate of 78.5 percent.”
Development and Validation of the AI Algorithm
This study builds on previous research where a model trained on voice recordings from over 1,000 individuals successfully identified cognitive impairment. The new algorithm focuses on transcribed audio recordings from 166 individuals aged 63 to 97 with MCI.
The researchers used machine learning to detect speech patterns associated with those who would develop Alzheimer’s. “By knowing in advance who would progress to Alzheimer’s, the team could train the algorithm to recognize these patterns.”
After being trained, the algorithm was tested on new speech samples; furthermore, factors such as age and self-reported sex were incorporated to refine its predictions. This method demonstrated the algorithm’s ability to foresee Alzheimer’s risk with notable accuracy.
Ioannis Paschalidis, a computer scientist at Boston University, explains that the predictive score indicates the probability of a person remaining stable or progressing to dementia. This predictive power shows the potential of AI in early Alzheimer’s detection.
Benefits of Early Detection and Future Prospects
Although there’s no cure for Alzheimer’s, early detection allows for earlier intervention with treatments to manage the disease. It also offers more opportunities to study the disease’s progression and enables at-risk individuals to join clinical trials.
“If further developed, this AI-driven speech analysis could become a quick, inexpensive, and accessible diagnostic tool, possibly integrated into a smartphone app,” Paschalidis emphasizes that predicting Alzheimer’s allows more time for intervention, aiming to maintain cognitive stability and prevent severe dementia. Moreover, cleaner data could further enhance the algorithm’s accuracy, ultimately contributing to a better understanding of Alzheimer’s onset.
Read the Original Article on: Science Alert
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