Temporal Modeling of Cognitive Decline: Health Patterns and Disease Progression in the All of Us Dataset

This study demonstrates the feasibility of deriving cognitive trajectories from All of Us data and reveals comorbidity profiles linked to progression speed. Findings support the development of explainable, fairness-aware AI models to improve early risk prediction. Future work will integrate these models into clinical workflows to support timely, targeted dementia care, particularly for groups historically affected by diagnostic delays and limited access.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70861_108259
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Temporal Modeling of Cognitive Decline: Health Patterns and Disease Progression in the All of Us Dataset

Zahra Rahemi, Mohadeseh Hashemi, Meisam Omidi
Alzheimer s & Dementia
Machine Learning in Healthcare
article

Temporal Modeling of Cognitive Decline: Health Patterns and Disease Progression in the All of Us Dataset

Zahra Rahemi, Mohadeseh Hashemi, Meisam Omidi
article en

Abstract

This study demonstrates the feasibility of deriving cognitive trajectories from All of Us data and reveals comorbidity profiles linked to progression speed. Findings support the development of explainable, fairness-aware AI models to improve early risk prediction. Future work will integrate these models into clinical workflows to support timely, targeted dementia care, particularly for groups historically affected by diagnostic delays and limited access.

Alzheimer s & DementiaVol. 21(S7)
Marquette University (US), Microgen (United States) (US), Clemson University (US)
Openalex Percentile: Top 19%
Machine Learning in Healthcare
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