Copyright: © 2025 by the authors. Licensee: Pirogov University.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (CC BY).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (CC BY).
ORIGINAL RESEARCH
Potential of the Addenbrooke's Cognitive Scale in the differential diagnosis of normal aging, mild cognitive impairment, Parkinson's disease and dementia.
About authors
1 State Budgetary Healthcare Institution of the Yaroslavl Region "Tutaevskaya Central Regional Hospital"
2 Federal State Budgetary Institution 'Clinical Hospital' of the Presidential Property Management Department of the Russian Federation
About paper
The authors declare no funding.
The authors declare no obvious or potential conflicts of interest related to the publication of this article.
Received: 2024-11-03
Accepted: 2024-12-15
Published online: 2025-01-06
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This paper considers the possibility of using artificial intelligence for differential diagnosis of normal aging, mild cognitive impairment, Parkinson's disease and dementia.
The study analyzed 77 protocols of ACE-III neuropsychological examination and applied modern methods of statistical analysis, machine learning and data processing. The results showed that the machine learning model has an average level of accuracy but needs to be improved to increase its effectiveness in diagnosing some groups of patients.
The research emphasizes the prospects of developing machine learning models for differential diagnostics based on ACE-III, however, it points out the need for additional features for more accurate diagnosis of certain diseases.
Keywords: differential diagnosis, artificial intelligence, machine learning, neuropsychological testing, Addenbrooke's Cognitive Examination-Revised