The representational bottleneck in rehabilitation AI: from human-cognitive proxies to pathway-based clinical representations.

Yang EJ, Chung SH

DOI: 10.3389/fdgth.2026.1917999
Published: 2026
Container: Frontiers in digital health
Publisher: Not recorded
Open access: yes

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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.3389/fdgth.2026.1917999,
  title = {The representational bottleneck in rehabilitation AI: from human-cognitive proxies to pathway-based clinical representations.},
  author = {Yang EJ and Chung SH},
  year = {2026},
  journal = {Frontiers in digital health},
  doi = {10.3389/fdgth.2026.1917999},
  url = {https://doi.org/10.3389/fdgth.2026.1917999}
}

RIS

TY  - JOUR
TI  - The representational bottleneck in rehabilitation AI: from human-cognitive proxies to pathway-based clinical representations.
AU  - Yang EJ
AU  - Chung SH
PY  - 2026
JO  - Frontiers in digital health
DO  - 10.3389/fdgth.2026.1917999
UR  - https://doi.org/10.3389/fdgth.2026.1917999
ER  -

APA

EJ, Y., & SH, C. (2026). The representational bottleneck in rehabilitation AI: from human-cognitive proxies to pathway-based clinical representations.. Frontiers in digital health. https://doi.org/10.3389/fdgth.2026.1917999

Source records

pubmed · retrieved 2026-09-25T08:53:26.401Z