A Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease

• URL: http://arxiv.org/abs/2607.29530v1
• Date: Fri, 31 Jul 2026 15:29:22 GMT
• Title: A Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease
• Abstract summary: We introduce an automated pipeline that extracts knowledge about potential Alzheimer's disease (AD) progression indicators directly from audio recordings of verbal fluency tests.<n>Our method uses pretrained foundation models to process raw audio and extract clinically relevant variables to construct a Bayesian Network (BN)<n>This BN is used to reason about the AD progression markers and infer their qualitative relationships.
• Score: 6.870812356071618
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Identifying reliable Alzheimer's disease (AD) markers typically requires manual, labor-intensive transcription and expert analysis, limiting its scale. We introduce an automated pipeline that extracts qualitative knowledge about potential AD progression indicators directly from audio recordings of verbal fluency tests. Our method uses pretrained foundation models to process raw audio and extract clinically relevant variables to construct a Bayesian Network (BN); this BN is used to reason about the AD progression markers and infer their qualitative relationships. Our system successfully recovers known clinical knowledge and identifies novel relationships between linguistic markers.

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