<ul data-eligibleForWebStory="true"><li>Alzheimer's dementia (AD) impacts language ability and is a neurodegenerative disorder with cognitive decline.</li><li>This study focuses on using a large language model (LLM), Mistral-7B, for AD detection through paired perplexity method.</li><li>The approach presented in this work improves detection accuracy by 3.33% compared to the best current method and by 6.35% over the top-ranked method from the ADReSS 2020 challenge benchmark.</li><li>The proposed approach provides a clear and interpretable decision boundary for AD detection, unlike other methods with opaque decision-making processes.</li><li>Analysis shows that the LLMs utilized have learned the unique language patterns of AD speakers, enhancing model interpretation and data augmentation possibilities.</li></ul>

Alzheimer's Dementia Detection Using Perplexity from Paired Large Language Models

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