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

arXiv 2607.29530 ↗First posted 31 Jul 2026cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 45 references that are in the map. First posted on arXiv 31 Jul 2026.

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References · 15

  1. 2017Attention Is All You Needcited by 59,932
  2. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  3. 2023A Comprehensive Overview of Large Language Modelscited by 639
  4. 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 492
  5. 2025MedGemma Technical Reportcited by 398
  6. 2020Neurosymbolic AI: The 3rd Wavecited by 253
  7. 2013Learning Bayesian Networks: The Combination of Knowledge and Statistical Datacited by 185
  8. 2023Large Language Models for Generative Information Extraction: A Surveycited by 183
  9. 2021From Statistical Relational to Neurosymbolic Artificial Intelligence: a Surveycited by 72
  10. 2023What's Left? Concept Grounding with Logic-Enhanced Foundation Modelscited by 33
  11. 2025SLOT: Structuring the Output of Large Language Modelscited by 18
  12. 2025Synthesizing Visual Concepts as Vision-Language Programscited by 6
3 more
  1. 2024A Unified Framework for Human-Allied Learning of Probabilistic Circuitscited by 5
  2. 2026Challenges in Automatic Speech Recognition for Adults with Cognitive Impairmentcited by 3
  3. 2023High-throughput Biomedical Relation Extraction for Semi-Structured Web Articles Empowered by Large Language Modelscited by 1

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