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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Methods for assessing impaired insight in Alzheimer's disease--a critical review]
Hanna Leicht1, Hermann-Josef Gertz
1Medizinische Fakultät, Universität Leipzig. Hanna.Leicht@medizin.uni-leipzig.de
Objective:
Impaired insight (anosognosia) is frequently present in Alzheimer's disease. However, established instruments for diagnosing anosognosia are lacking.
Method:
This article reviews the literature on impaired insight in Alzheimer's disease with a focus on assessment methods that have been applied to its study.
Results:
The primary methods for assessing anosognosia are clinical judgment, comparison of patient and caregiver reports, and comparison of patients' self-assessment and task performance.
Conclusions:
While simple approaches such as expert rating scales can be appropriate for clinical practice, more elaborate procedures in research may shed light on the cognitive mechanisms involved in anosognosia. Previous results have shown that unawareness of deficits affects cognitive and emotional domains as well as activities of daily living, thus any diagnostic instrument should capture these different aspects. However, methodological issues such as the objectivity of caregiver reports or patients' ability to assess their own performance need to be considered in order to obtain reliable data.
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