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Updated: Oct 9, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Collecting information: optimizing outcomes, screening options, or facilitating discrimination?
1Department of Psychology, University College London, Gower Street, London WC1E 6BT, U.K. n.harvey@ucl.ac.uk
Abstract:
Collection of information prior to a decision may be integrated into a compensatory choice process; if it is, the information packet that is collected should be the one that produces the highest net gain. Alternatively, information may be collected in order to screen out options that fail to meet minimum standards; if this is the case, people should not choose options on which they have not collected available information. We tested these and other predictions from the two approaches in four experiments. Participants were given specific information about three attributes of each choice option but only probabilistic information about a fourth one. They rated attractiveness of options, decided whether to collect specific information about the fourth attribute of each one, rated options again, and then selected one of them. Data were consistent with neither of the above approaches. Instead they suggested that people collect information in order to facilitate their ability to discriminate between the attractiveness of options.
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