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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The impact of mild cognitive impairment on decision making in two gambling tasks
Laura Zamarian1, Elisabeth M Weiss, Margarete Delazer
1Clinical Department of Neurology, Medical University Innsbruck, Anichstrasse 35, 6020 Innsbruck, Austria. laura.zamarian@uki.at
Objectives:
This study aimed to investigate whether patients with mild cognitive impairment (MCI) present difficulties in making decisions under ambiguity and under risk.
Methods:
Performance of MCI patients in the Iowa Gambling Task (IGT) and in the Probability-Associated Gambling Task-Revised (PAG-R) was compared with performance of healthy aging peers.
Results:
In the IGT, controls made increasingly frequent advantageous selections over time; MCI patients selected randomly from advantageous and disadvantageous decks, with no significant change in performance over time. In the PAG-R, controls decided advantageously in conditions of both (low, high) winning probabilities; patients made less advantageous decisions than controls in conditions of low winning probability.
Discussion:
In the decision under ambiguity task (IGT), MCI patients experienced difficulties in learning from feedback and in maintaining an advantageous strategy over time. In the decision under risk task (PAG-R), patients had problems in integrating information from different sources and in adapting their strategy to changes in the decision situation. In summary, MCI patients present difficulties in advantageous decision making that resemble those reported for patients with mild dementia.
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