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Predicting post-stroke aphasia from brain imaging

Author

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  • Monica D. Rosenberg

    (University of Chicago)

  • Hayoung Song

    (University of Chicago)

Abstract

Stroke can lead to debilitating consequences, including loss of language. An important goal of stroke research is to use machine learning to predict outcomes and response to therapy. A new study compares different approaches to predicting post-stroke outcomes and highlights the need for systematic optimization and validation to ultimately translate scientific insights to clinical settings.

Suggested Citation

  • Monica D. Rosenberg & Hayoung Song, 2020. "Predicting post-stroke aphasia from brain imaging," Nature Human Behaviour, Nature, vol. 4(7), pages 675-676, July.
    • Handle: RePEc:nat:nathum:v:4:y:2020:i:7:d:10.1038_s41562-020-0902-1
    DOI: 10.1038/s41562-020-0902-1
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