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Extending the usefulness of the verbal memory test: The promise of machine learning

Permanent lenke
https://hdl.handle.net/10037/22071
DOI
https://doi.org/10.1016/j.psychres.2021.113743
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article.pdf (1.217Mb)
Publisert versjon (PDF)
Dato
2021-01-19
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Forfatter
Chandler, Chelsea; Holmlund, Terje Bektesevic; Foltz, Peter W.; Cohen, Alex S.; Elvevåg, Brita
Sammendrag
The evaluation of verbal memory is a core component of neuropsychological assessment in a wide range of clinical and research settings. Leveraging story recall to assay neurocognitive function could be made more useful if it were possible to administer frequently (i.e., would allow for the collection of more patient data over time) and automatically assess the recalls with machine learning methods. In the present study, we evaluated a novel story recall test with 24 parallel forms that was deployed using smart devices in 94 psychiatric inpatients and 80 nonpatient adults. Machine learning and vector-based natural language processing methods were employed to automate test scoring, and performance using these methods was evaluated in their incremental validity, criterion validity (i.e., convergence with trained human raters), and parallel forms reliability. Our results suggest moderate to high consistency across the parallel forms, high convergence with human raters (r values ~ 0.89), and high incremental validity for discriminating between groups. While much work remains, the present findings are critical for implementing an automated, neuropsychological test deployable using remote technologies across multiple and frequent administrations.
Forlag
Elsevier
Sitering
Chandler, Holmlund, Foltz, Cohen, Elvevåg. Extending the usefulness of the verbal memory test: The promise of machine learning. Psychiatry Research. 2021;297:113743:1-7
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  • Artikler, rapporter og annet (klinisk medisin) [1974]
Copyright 2021 The Author(s)

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