Cognitive Assessment of Dementia Patients Using Large Language Models

This study highlights the potential of LLMs in predicting cognitive function for dementia patients using EHRs. Larger LLMs showed superior performance, while the CoT and summary strategies improved interpretability but may slightly impair performance. The results highlight the necessity for further adoption and optimization of LLM modeling and reasoning strategies to better handle clinical text, minimizing hallucinations and improving reliability. Integrating LLMs into cognitive assessment workflows could enhance efficiency and accessibility, supporting more effective dementia care and management.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70858_103769
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Cognitive Assessment of Dementia Patients Using Large Language Models

Richard Wyss, Jiageng Wu, Josh C. H. Lin, Jie Yang
Alzheimer s & Dementia
Dementia and Cognitive Impairment Research
article

Cognitive Assessment of Dementia Patients Using Large Language Models

Richard Wyss, Jiageng Wu, Josh C. H. Lin, Jie Yang
article en

Abstract

This study highlights the potential of LLMs in predicting cognitive function for dementia patients using EHRs. Larger LLMs showed superior performance, while the CoT and summary strategies improved interpretability but may slightly impair performance. The results highlight the necessity for further adoption and optimization of LLM modeling and reasoning strategies to better handle clinical text, minimizing hallucinations and improving reliability. Integrating LLMs into cognitive assessment workflows could enhance efficiency and accessibility, supporting more effective dementia care and management.

Alzheimer s & DementiaVol. 21(S4)
Brigham and Women's Hospital (US)
Openalex Percentile: Top 32%
Dementia and Cognitive Impairment Research
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