A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers

IntroductionInadequate primary care infrastructure and training in China and misconceptions about aging lead to high mis−/under-diagnoses and serious time delays for dementia patients, imposing significant burdens on family members and medical carers.Main bodyA flowchart integrating rural and urban...

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Main Authors: Pinya Lu, Xiaolu Lin, Xiaofeng Liu, Mingfeng Chen, Caiyan Li, Hongqin Yang, Yuhua Wang, Xuemei Ding
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Aging Neuroscience
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Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2025.1554834/full
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author Pinya Lu
Xiaolu Lin
Xiaofeng Liu
Mingfeng Chen
Caiyan Li
Hongqin Yang
Yuhua Wang
Xuemei Ding
author_facet Pinya Lu
Xiaolu Lin
Xiaofeng Liu
Mingfeng Chen
Caiyan Li
Hongqin Yang
Yuhua Wang
Xuemei Ding
author_sort Pinya Lu
collection DOAJ
description IntroductionInadequate primary care infrastructure and training in China and misconceptions about aging lead to high mis−/under-diagnoses and serious time delays for dementia patients, imposing significant burdens on family members and medical carers.Main bodyA flowchart integrating rural and urban areas of China dementia care pathway is proposed, especially spotting the obstacles of mis/under-diagnoses and time delays that can be alleviated by data-driven computational strategies. Artificial intelligence (AI) and machine learning models built on dementia data are succinctly reviewed in terms of the roadmap of dementia care from home, community to hospital settings. Challenges and corresponding recommendations to clinical transformation are then reported from the viewpoint of diverse dementia data integrity and accessibility, as well as models’ interpretability, reliability, and transparency.DiscussionDementia cohort study along with developing a center-crossed dementia data platform in China should be strongly encouraged, also data should be publicly accessible where appropriate. Only be doing so can the challenges be overcome and can AI-enabled dementia research be enhanced, leading to an optimized pathway of dementia care in China. Future policy-guided cooperation between researchers and multi-stakeholders are urgently called for dementia 4E (early-screening, early-assessment, early-diagnosis, and early-intervention).
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language English
publishDate 2025-03-01
publisher Frontiers Media S.A.
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series Frontiers in Aging Neuroscience
spelling doaj-art-5fd326a17cb44cd487e327b9f2c2f1fc2025-08-20T02:00:47ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652025-03-011710.3389/fnagi.2025.15548341554834A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriersPinya Lu0Xiaolu Lin1Xiaofeng Liu2Mingfeng Chen3Caiyan Li4Hongqin Yang5Yuhua Wang6Xuemei Ding7Fujian Provincial Engineering Research Centre for Public Service Big Data Mining and Application, Fujian Provincial University Engineering Research Center for Big Data Analysis and Application, Fujian Normal University, Fuzhou, ChinaFujian Provincial Engineering Research Centre for Public Service Big Data Mining and Application, Fujian Provincial University Engineering Research Center for Big Data Analysis and Application, Fujian Normal University, Fuzhou, ChinaDepartment of Radiology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaDepartment of Neurology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaDepartment of Neurology, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, ChinaKey Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, ChinaKey Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory for Photonics Technology, Fujian Normal University, Fuzhou, ChinaIntelligent Systems Research Centre, School of Computing, Engineering and Intelligent Systems, Ulster University, Londonderry, United KingdomIntroductionInadequate primary care infrastructure and training in China and misconceptions about aging lead to high mis−/under-diagnoses and serious time delays for dementia patients, imposing significant burdens on family members and medical carers.Main bodyA flowchart integrating rural and urban areas of China dementia care pathway is proposed, especially spotting the obstacles of mis/under-diagnoses and time delays that can be alleviated by data-driven computational strategies. Artificial intelligence (AI) and machine learning models built on dementia data are succinctly reviewed in terms of the roadmap of dementia care from home, community to hospital settings. Challenges and corresponding recommendations to clinical transformation are then reported from the viewpoint of diverse dementia data integrity and accessibility, as well as models’ interpretability, reliability, and transparency.DiscussionDementia cohort study along with developing a center-crossed dementia data platform in China should be strongly encouraged, also data should be publicly accessible where appropriate. Only be doing so can the challenges be overcome and can AI-enabled dementia research be enhanced, leading to an optimized pathway of dementia care in China. Future policy-guided cooperation between researchers and multi-stakeholders are urgently called for dementia 4E (early-screening, early-assessment, early-diagnosis, and early-intervention).https://www.frontiersin.org/articles/10.3389/fnagi.2025.1554834/fulldementiaAlzheimer’s diseaseChina dementia care pathwaycomputational strategymachine learningoptimization
spellingShingle Pinya Lu
Xiaolu Lin
Xiaofeng Liu
Mingfeng Chen
Caiyan Li
Hongqin Yang
Yuhua Wang
Xuemei Ding
A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
Frontiers in Aging Neuroscience
dementia
Alzheimer’s disease
China dementia care pathway
computational strategy
machine learning
optimization
title A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
title_full A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
title_fullStr A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
title_full_unstemmed A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
title_short A mini review of transforming dementia care in China with data-driven insights: overcoming diagnostic and time-delayed barriers
title_sort mini review of transforming dementia care in china with data driven insights overcoming diagnostic and time delayed barriers
topic dementia
Alzheimer’s disease
China dementia care pathway
computational strategy
machine learning
optimization
url https://www.frontiersin.org/articles/10.3389/fnagi.2025.1554834/full
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