ORIGINAL RESEARCH article
Front. Neurol.
Sec. Dementia and Neurodegenerative Diseases
Mobile Cognitive Assessment Demonstrates Diagnostic Equivalence to MMSE and MoCA Scales in Alzheimer's Disease Screening
Provisionally accepted
- 1Chongqing Key Laboratory of Ophthalmology, Chongqing Eye Institute, Chongqing, China
- 2The First Affiliated Hospital of Chongqing Medical University Yubei Hospital, Chongqing, China
- 3Sichuan Academy of Medical Sciences and Sichuan People's Hospital, Chengdu, China
- 4Xindu District People's Hospital of Chengdu, Chengdu, China
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Alzheimer's disease (AD), the most common neurodegenerative disorder, poses significant challenges for early screening due to the clinical and environmental constraints of traditional neuropsychological assessments. This study developed a mobile terminal-based cognitive assessment system (mCAS) and prospectively validated its screening efficacy through a diagnostic trial. We recruited 63 memory clinic patients (aged 20–75 years), all of whom independently completed mCAS testing after undergoing standardized MMSE and MoCA evaluations. Through a systematic review of 10 existing mild cognitive impairment (MCI) screening tools, we extracted 25 test items to construct the assessment framework. Our results demonstrated that, under the optimal Gradient Boosting model, mCAS achieved an area under the curve (AUC) of 0.884 for discriminating MCI while maintaining diagnostic equivalence in sensitivity compared to conventional instruments (P > 0.05 in all pairwise comparisons). Specificity was significantly lower than MoCA only for MCI identification (P = 0.027). The system's core innovations include: 1. A multimodal digital assessment framework that overcomes the environmental limitations of conventional scales; 2. Self-administration capability in non-medical settings; and 3. A dynamic cognitive baseline model to facilitate longitudinal monitoring. mCAS provides a convenient screening solution for early AD detection, with significant potential particularly in resource-limited regions. Future multicenter validation and biomarker integration studies are warranted.
Keywords: Alzheimer's disease, Cognitive screening, machine learning, MCAS, Mild Cognitive Impairment, Mobile Cognitive Assessment
Received: 03 Dec 2025; Accepted: 16 Feb 2026.
Copyright: © 2026 Zhang, Chen, Xie, Chang, Huang and Zhang. 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: Min Zhang
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