References & Citations
Computer Science > Machine Learning
Title: ADMarker: A Multi-Modal Federated Learning System for Monitoring Digital Biomarkers of Alzheimer's Disease
(Submitted on 23 Oct 2023 (v1), last revised 12 Apr 2024 (this version, v3))
Abstract: Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms for detecting multidimensional AD digital biomarkers in natural living environments. ADMarker features a novel three-stage multi-modal federated learning architecture that can accurately detect digital biomarkers in a privacy-preserving manner. Our approach collectively addresses several major real-world challenges, such as limited data labels, data heterogeneity, and limited computing resources. We built a compact multi-modality hardware system and deployed it in a four-week clinical trial involving 91 elderly participants. The results indicate that ADMarker can accurately detect a comprehensive set of digital biomarkers with up to 93.8% accuracy and identify early AD with an average of 88.9% accuracy. ADMarker offers a new platform that can allow AD clinicians to characterize and track the complex correlation between multidimensional interpretable digital biomarkers, demographic factors of patients, and AD diagnosis in a longitudinal manner.
Submission history
From: Xiaomin Ouyang Dr. [view email][v1] Mon, 23 Oct 2023 19:07:33 GMT (3136kb,D)
[v2] Wed, 27 Mar 2024 21:56:59 GMT (6544kb,D)
[v3] Fri, 12 Apr 2024 06:25:43 GMT (6544kb,D)
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