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June 20, 2026Intelligence-Based MedicineOpen Access

Artificial Intelligence in the Automatic Diagnosis of Dementia Disorders: A Scoping Review of Techniques, Applications, and Challenges

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Authors

AGAlexandra GenniAristotle University of ThessalonikiMTMagda TsolakiAristotle University of ThessalonikiPSPanagiotis SarigiannidisUniversity of Western Macedonia

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Implication

Scoping review evaluates AI models for dementia diagnosis, highlighting challenges and clinical applications.

Key Points

  • This review aims to evaluate various artificial intelligence techniques used for diagnosing dementia disorders.
  • Conducted a scoping review in adherence to PRISMA-ScR guidelines.
  • Searched Scopus, PubMed, and IEEE Xplore for peer-reviewed articles from 2014 to 2025.
  • Included 15 studies for narrative synthesis on AI models for dementia diagnosis.
  • AI models achieved AUCs between 0.88–0.98 for binary classification of Alzheimer's disease versus cognitively normal cases.
  • Multi-etiology differential diagnosis reached AUCs of 0.82–0.96, while MCI-to-AD prognosis had AUCs of 0.74–0.84.
  • Challenges included external generalisation, label noise, and fairness gaps across examined studies.

Cite This Study

Genni et al. (2026) studied this question.

synapsesocial.com/papers/6a362d9ddb0793dc1a535cc5https://doi.org/10.1016/j.ibmed.2026.100414
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