REVIEW article
Front. Mol. Med.
Sec. Molecular Mechanisms of Neurodegeneration
Volume 5 - 2025 | doi: 10.3389/fmmed.2025.1671337
This article is part of the Research TopicEmpowering Precision Medicine in Neurodegenerative Diseases via Data Sharing Strategies and AI InnovationsView all articles
AI-enabled Resilience Modeling for Brain Health
Provisionally accepted
- 1Simon Fraser University, Burnaby, Canada
- 2Resilience Analytics, Boston, United States
- 3Carnagie Mellon University, Pittsburg, United States
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One development in the growing field of Alzheimer’s Disease and related neurological disorders (ADRD) is the consideration of brain resilience, the ability to respond to and recover from adversity, which builds on a growing literature on the role of lifestyle behaviours in ADRD prevention and response. This paper reviews definitions of ‘brain health’ and integrates these with innovations in resilience system models applied to ADRD. Based on a socio-ecological framework that links physiological, behavioral, economic, and social determinants of mental health, we propose a unified model of resilience and aging in this field. We contend that applications of a resilience analytical approach to brain health require innovation in Artificial Intelligence (AI) to harness the full potential of immense interdisciplinary data mining opportunities. These include: development of digital twins, precision health analytics, AI sensors, and Multimodal Large Language Models (MLLM), knowledge graph technologies, and cognitive/decision science modeling. We apply this model to research and clinical examples to elucidate its potential value, requirements, risks, and challenges in developing new research agendas.
Keywords: Brain health, AI-models, resilience, Research agenda, Challenges
Received: 22 Jul 2025; Accepted: 08 Sep 2025.
Copyright: © 2025 Wister, Pinigina, Liang and Linkov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Andrew Wister, wister@sfu.ca
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