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Researchers Use Ai To Identify

Researchers Use AI to Identify Early Alzheimer’s Signs

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Researchers Use AI to Identify Early Alzheimer’s Signs Through a Patient’s Voice

 

 

 

Discover how Boston University researchers use AI voice analysis to predict Alzheimer’s disease up to six years early with 78.5% accuracy.

AI Detects Early Alzheimer’s in Speech

Researchers at Boston University have developed an AI system that identifies early symptoms of Alzheimer’s disease by analysing patient speech. This breakthrough offers hope for earlier diagnosis when treatment options can be more effective.

Why Early Detection Matters

Currently, there is no cure for Alzheimer’s disease. However, detecting it early provides patients with more treatment choices. For example, patients can join clinical trials aimed at slowing or stopping disease progression. Early diagnosis also helps families plan and manage care better.

How the AI System Works

The AI combines machine learning and natural language processing (NLP) to analyse voice recordings from patients. By examining patterns in speech, the system predicts whether a patient will develop Alzheimer’s within six years.

In the study, the AI successfully identified Alzheimer’s in 166 patients with 78.5% accuracy. This automated method could make screening for mild cognitive impairment (MCI) easier and more accessible.

A Fully Automated and Accessible Tool

According to the researchers, the AI offers a fully automated process. It has the potential to be inexpensive and widely available. Moreover, it could allow remote assessments, where patients submit voice recordings to physicians for evaluation.

This approach would be especially valuable in reaching patients who cannot visit clinics regularly.

Alarming Alzheimer’s Projections

By 2050, the number of Americans with Alzheimer’s is expected to nearly double from 7 million to 13 million. This makes early detection even more critical for healthcare planning and patient support.

The Research Approach: Speech and Data Analysis

To test AI’s potential for early diagnosis, researchers analysed voice recordings collected during neuropsychological exams. They also incorporated basic demographic data such as age, sex, and education level.

The AI system used speech recognition to convert audio into text. Then, language models processed the text to identify subtle signs of cognitive decline.

This multimodal approach resulted in a fully automated assessment capable of pinpointing patients most at risk for Alzheimer’s.

Key Findings: Who Is Most at Risk?

The model revealed that older women with lower education levels are more likely to develop Alzheimer’s. It also highlighted that women carrying the APOE-ε4 gene face higher risks.

Additionally, the risk increases significantly with age. The AI predicted that 19% of patients aged 75 to 84 and 35% of those over 85 would likely develop Alzheimer’s.

Conclusion: AI’s Promising Role in Alzheimer’s Prediction

“Our study demonstrates the potential of using automatic speech recognition and natural language processing techniques to develop a prediction tool,” the researchers concluded. This tool can help identify individuals with MCI who face higher risks of progressing to Alzheimer’s.

As AI technology advances, it may soon become a routine part of early screening, offering hope to millions at risk.

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