About GPT-3 Alzheimer

The article titled “Predicting dementia from spontaneous speech using large language models” by Felix Agbavor and Hualou Liang, published in PLOS Digital Health, explores the potential of GPT-3, a language model developed by OpenAI, in predicting Alzheimer’s disease (AD) through speech analysis. The study demonstrates the effectiveness of text embedding powered by GPT-3 in distinguishing individuals with AD from healthy controls and inferring cognitive testing scores based on speech data.

Here are four key features of the study

  1. GPT-3 for Alzheimer’s Detection: The study shows that GPT-3 can be used to predict dementia from spontaneous speech. This is achieved by leveraging the vast semantic knowledge encoded in the GPT-3 model to generate text embeddings, which capture the semantic meaning of the input.
  2. Distinguishing AD from Healthy Controls: The text embeddings generated by GPT-3 can be reliably used to distinguish individuals with AD from healthy controls, solely based on speech data.
  3. Inferring Cognitive Testing Scores: The study also demonstrates that GPT-3 can be used to infer a subject’s cognitive testing score, again solely based on speech data.
  4. Outperforming Conventional Approaches: The text embeddings powered by GPT-3 considerably outperform the conventional feature-based approach and even perform competitively with the mainstream use of fine-tuned models. This suggests a huge potential to develop AI-driven tools for early diagnosis of dementia, thereby improving the quality of life for individuals with dementia.