Service-Specific Heterogeneity in Sepsis Variable Significance and Machine Learning Model Performance: A Stratified Analysis of the BIAlert Cohort.

Borges-Sa M, Macias-Fassio E, Delgado A, Salas-Sosa S, Aranda M, Socias A, Del Castillo A, Giglio A

Open source

DOI
10.3390/jcm15134904
Published
2026 Jun 24
Container
Journal of clinical medicine
Publisher
Not recorded
Open access
yes

Credibility signals

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

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3390/jcm15134904,
  title = {Service-Specific Heterogeneity in Sepsis Variable Significance and Machine Learning Model Performance: A Stratified Analysis of the BIAlert Cohort.},
  author = {Borges-Sa M and Macias-Fassio E and Delgado A and Salas-Sosa S and Aranda M and Socias A and Del Castillo A and Giglio A},
  year = {2026},
  journal = {Journal of clinical medicine},
  doi = {10.3390/jcm15134904},
  url = {https://doi.org/10.3390/jcm15134904}
}

RIS

TY  - JOUR
TI  - Service-Specific Heterogeneity in Sepsis Variable Significance and Machine Learning Model Performance: A Stratified Analysis of the BIAlert Cohort.
AU  - Borges-Sa M
AU  - Macias-Fassio E
AU  - Delgado A
AU  - Salas-Sosa S
AU  - Aranda M
AU  - Socias A
AU  - Del Castillo A
AU  - Giglio A
PY  - 2026
JO  - Journal of clinical medicine
DO  - 10.3390/jcm15134904
UR  - https://doi.org/10.3390/jcm15134904
ER  - 

APA

M, B., E, M., A, D., S, S., M, A., A, S., A, D. C., & A, G. (2026). Service-Specific Heterogeneity in Sepsis Variable Significance and Machine Learning Model Performance: A Stratified Analysis of the BIAlert Cohort.. Journal of clinical medicine. https://doi.org/10.3390/jcm15134904

Source records