mlsanityData to 7 Oct 2026

A Systematic Review of NLP for Dementia -- Tasks, Datasets and Opportunities

arXiv 2409.19737 ↗First posted 29 Sep 2024cs.CLcited by 4

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Abstract (arXiv)

The close link between cognitive decline and language has fostered long-standing collaboration between the NLP and medical communities in dementia research. To examine this, we reviewed over 240 papers applying NLP to dementia-related efforts, drawing from medical, technological, and NLP-focused literature. We identify key research areas, including dementia detection, linguistic biomarker extraction, caregiver support, and patient assistance, showing that half of all papers focus solely on dementia detection using clinical data. Yet, many directions remain unexplored -- artificially degraded language models, synthetic data, digital twins, and more. We highlight gaps and opportunities around trust, scientific rigor, applicability and cross-community collaboration. We raise ethical dilemmas in the field, and highlight the diverse datasets encountered throughout our review -- recorded, written, structured, spontaneous, synthetic, clinical, social media-based, and more. This review aims to inspire more creative, impactful, and rigorous research on NLP for dementia.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 33 of its 216 references that are in the map. First posted on arXiv 29 Sep 2024.

Builds on

33 of 216 references.

References · 33

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21 more
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  2. 2020The INESC-ID Multi-Modal System for the ADReSS 2020 Challengecited by 15
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Dementia Through Different Eyes: Explainable Modeling of Human and LLM Perceptions for Early Awarenesscited by 2
  2. 2025PersonaDrift: A Benchmark for Temporal Anomaly Detection in Language-Based Dementia Monitoringcited by 0
  3. 2026ADRD-Bench: A Preliminary LLM Benchmark for Alzheimer's Disease and Related Dementiascited by 0
  4. 2026Forgotten Words: Benchmarking NeoBERT for Dementia Detection in Low-Resource Conversational Filipino and English Speechcited by 0