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Updated: May 7, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
A Novel Combined Audiovisual-Semantic Digital Tool for Early-Stage Cognitive Decline Detection: Development and
Qiwei Wu1,2, Binyu Zhao1,2, Zihao Zheng1,2
1Department of Nursing, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Hushan Road 200, Yiwu, Zhejiang Province, China.
Background:
Dementia poses a significant public health challenge. Early detection is crucial for timely intervention but remains difficult in community settings, as many existing cognitive screening tools are either insufficiently sensitive to subtle decline or too burdensome for widespread use.
Objective:
This study aimed to develop and validate a novel combined audiovisual-semantic digital tool for rapid and acceptable community-based screening of cognitive decline in older adults.
Methods:
A total of 156 older adults completed 6 progressively complex task variants shifting from unimodal to multimodal stimuli and from basic to superordinate semantic categorization. Performance was measured using reaction time, accuracy, false alarms, and inverse efficiency. Diagnostic utility was assessed via logistic regression and receiver operating characteristic curve analysis, whereas qualitative interviews evaluated acceptability.
Results:
Task outcomes showed significant declines across the cognitive continuum from no cognitive impairment to mild cognitive impairment to dementia (P<.001). The integrated audiovisual-semantic condition at the basic categorization level reliably differentiated cognitive groups and achieved higher area under the curve values for distinguishing no cognitive impairment from cognitive impairment and mild cognitive impairment from dementia compared to basic-level tasks. Incorporating semantic processing enhanced diagnostic discrimination. Participant feedback was highly positive, with 48.7% (76/156) describing the tasks as "fun/interesting."
Conclusions:
The audiovisual-semantic integrated digital tool is a valid, well-accepted, and time-efficient instrument for cognitive screening in older adults. Its design, which increases cognitive load through multimodal and semantic integration, improves sensitivity to early decline, supporting its potential for practical community application.
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