Optimizing predictive performance without sacrificing explainability: Comparing logistic regression and ensemble decision trees for abdominal aortic aneurysm repair outcomes.

Jeon BB, Kottakota AK, Kerr KE, Gueldner PH, Guffey MJ, Sen I, Liang NL, Vorp DA, Chung TK.

Open source

DOI
10.1016/j.jvsvi.2025.100300
Published
2026-02-27
Container
JVS Vasc Insights
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1016/j.jvsvi.2025.100300,
  title = {Optimizing predictive performance without sacrificing explainability: Comparing logistic regression and ensemble decision trees for abdominal aortic aneurysm repair outcomes.},
  author = {Jeon BB and  Kottakota AK and  Kerr KE and  Gueldner PH and  Guffey MJ and  Sen I and  Liang NL and  Vorp DA and  Chung TK.},
  year = {2026},
  journal = {JVS Vasc Insights},
  doi = {10.1016/j.jvsvi.2025.100300},
  url = {https://doi.org/10.1016/j.jvsvi.2025.100300}
}

RIS

TY  - JOUR
TI  - Optimizing predictive performance without sacrificing explainability: Comparing logistic regression and ensemble decision trees for abdominal aortic aneurysm repair outcomes.
AU  - Jeon BB
AU  -  Kottakota AK
AU  -  Kerr KE
AU  -  Gueldner PH
AU  -  Guffey MJ
AU  -  Sen I
AU  -  Liang NL
AU  -  Vorp DA
AU  -  Chung TK.
PY  - 2026
JO  - JVS Vasc Insights
DO  - 10.1016/j.jvsvi.2025.100300
UR  - https://doi.org/10.1016/j.jvsvi.2025.100300
ER  - 

APA

BB, J., AK, K., KE, K., PH, G., MJ, G., I, S., NL, L., DA, V., & TK., C. (2026). Optimizing predictive performance without sacrificing explainability: Comparing logistic regression and ensemble decision trees for abdominal aortic aneurysm repair outcomes.. JVS Vasc Insights. https://doi.org/10.1016/j.jvsvi.2025.100300

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