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SCH: Fair and Interpretable Prediction of Alzheimer's Disease and MCI using LLMs

Award Number: R01AG091762
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2024
PERIOD OF PERFORMANCE END DATE: 05/31/2028

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SCH: Fair and Interpretable Prediction of Alzheimer's Disease and MCI using LLMs - This proposal aims to develop high-performing, fair, and interpretable large language models (LLMs) to detect Alzheimer's disease (AD) and its precursor stages. In doing so, its overarching goal is to advance healthcare through the innovative and responsible use of LLMs to recognize AD, mild cognitive impairment (MCI), and preclinical AD from transcribed unstructured speech samples, prioritizing fairness in their deployment. Evidence has demonstrated that language is impaired early in AD, including in the MCI and even prodromal AD stage. Moreover, recent natural language processing (NLP) approaches have shown that informative markers of this impairment can be captured from spontaneous speech samples. LLMs, a new cornerstone of NLP, have shown promise at addressing healthcare tasks, but concerns exist regarding their potential biases and poor explainability. We will test the use of LLMs to identify early stages of the AD trajectory from transcribed unstructured speech samples, making fairness and explainability a central piece of our aims. We hypothesize that the use of fair, explainable LLMs for early AD detection may overcome data constraints and interpretability issues common while enabling effective low-resource learning for this purpose. We will test this hypothesis through three aims: (1) building on our shared expertise and prior work, we will design LLM-based models for detecting MCI and dementia and explore their use in detecting the earliest preclinical stage; (2) we will enhance model fairness and interpretability through innovative demonstration example selection and domain-aligned instruction tuning techniques, and develop new methods for explaining LLM output in healthcare settings; and (3) we will validate our methods by assessing their alignment with clinical parameters related to AD and MCI. We will also perform a pioneering exploration of the extent to which our findings are repeatable beyond English settings. Expected outcomes include groundbreaking generalizable insights in NLP and AI fairness and interpretability, and domain-specific advances that could help ensure wide access to AD and MCI detection. This may lay groundwork for a low-cost, scalable, non-invasive alternative for cognitive health screening and reduce healthcare disparities via fairer access to high-quality cognitive health assessment. At an economic scale, this work may reduce long-term burden on the healthcare system and improve quality of life, benefitting individuals and society.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $285,796 )
2026	2026	UNIVERSITY OF ILLINOIS	809 S MARSHFIELD AVE M/C 551	CHICAGO	IL	60612	COOK	USA	Aging Research	000	3	6/3/2026	NON-COMPETING CONTINUATION	$285,796
														Subtotal = $285,796

Issue Date FY: 2025 ( Subtotal = $285,992 )
2025	2025	UNIVERSITY OF ILLINOIS	809 S MARSHFIELD AVE M/C 551	CHICAGO	IL	60612	COOK	USA	Aging Research	000	2	7/15/2025	NON-COMPETING CONTINUATION	$285,992
														Subtotal = $285,992

Issue Date FY: 2024 ( Subtotal = $300,506 )
2024	2024	UNIVERSITY OF ILLINOIS	809 S MARSHFIELD AVE M/C 551	CHICAGO	IL	60612	COOK	USA	Aging Research	000	1	7/25/2024	NEW	$300,506
														Subtotal = $300,506

Grand Total All Awards = $872,294

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SCH: Fair and Interpretable Prediction of Alzheimer's Disease and MCI using LLMs

Award Number: R01AG091762

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/01/2024

PERIOD OF PERFORMANCE END DATE: 05/31/2028

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