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Updated: Aug 27, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[The state of the oral cavity in early diagnosis and predicting cognitive disorders.]
V S Myakotnykh1, A P Sidenkova1, M P Kharitonova1
1Ural State Medical University, 3 Repin str., Yekaterinburg 620028, Russian Federation,
Abstract:
A review of the literature on the problem of the use of non-invasive technologies in early diagnosis and prediction of age-associated cognitive decline associated with Alzheimer's disease is presented. The main attention is paid to the study of the buccal epithelium, oral fluid, as surrogate models of degenerative lesions of cerebral structures, as well as determining the role of oral microorganisms in the formation and development of cognitive disorders. An original hypothesis of neurodegenerative lesions of cerebral structures is presented, on the basis of which an algorithm for studying the state of the oral cavity is proposed in order to detect and predict cognitive deficits as early as possible.
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