Uncertainty Quantification in Machine Learning for Biosignal Applications - A Review.

de Jong IP, Sburlea AI, Valdenegro-Toro M

DOI: 10.1007/s41666-026-00249-5
Published: 2026 Dec
Container: Journal of healthcare informatics research
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1007/s41666-026-00249-5,
  title = {Uncertainty Quantification in Machine Learning for Biosignal Applications - A Review.},
  author = {de Jong IP and Sburlea AI and Valdenegro-Toro M},
  year = {2026},
  journal = {Journal of healthcare informatics research},
  doi = {10.1007/s41666-026-00249-5},
  url = {https://doi.org/10.1007/s41666-026-00249-5}
}

RIS

TY  - JOUR
TI  - Uncertainty Quantification in Machine Learning for Biosignal Applications - A Review.
AU  - de Jong IP
AU  - Sburlea AI
AU  - Valdenegro-Toro M
PY  - 2026
JO  - Journal of healthcare informatics research
DO  - 10.1007/s41666-026-00249-5
UR  - https://doi.org/10.1007/s41666-026-00249-5
ER  -

APA

IP, D. J., AI, S., & M, V. (2026). Uncertainty Quantification in Machine Learning for Biosignal Applications - A Review.. Journal of healthcare informatics research. https://doi.org/10.1007/s41666-026-00249-5

Source records

pubmed · retrieved 2026-11-10T11:11:56.936Z