Resolving Interpretation Challenges in Machine Learning Feature Selection With an Iterative Approach in Biomedical Pain Data

Jörn Lötsch, André Himmelspach, Dario Kringel

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DOI: 10.1002/ejp.70221
Published: 2026-01-26
Container: European Journal of Pain
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/ejp.70221,
  title = {Resolving Interpretation Challenges in Machine Learning Feature Selection With an Iterative Approach in Biomedical Pain Data},
  author = {Jörn Lötsch and André Himmelspach and Dario Kringel},
  year = {2026},
  journal = {European Journal of Pain},
  doi = {10.1002/ejp.70221},
  url = {https://doi.org/10.1002/ejp.70221}
}

RIS

TY  - JOUR
TI  - Resolving Interpretation Challenges in Machine Learning Feature Selection With an Iterative Approach in Biomedical Pain Data
AU  - Jörn Lötsch
AU  - André Himmelspach
AU  - Dario Kringel
PY  - 2026
JO  - European Journal of Pain
DO  - 10.1002/ejp.70221
UR  - https://doi.org/10.1002/ejp.70221
ER  -

APA

Lötsch, J., Himmelspach, A., & Kringel, D. (2026). Resolving Interpretation Challenges in Machine Learning Feature Selection With an Iterative Approach in Biomedical Pain Data. European Journal of Pain. https://doi.org/10.1002/ejp.70221

Source records

crossref · retrieved 2026-09-26T23:51:26.380Z