Logistic regression, mean imputation (INSPIRE authors' script) on inspire-mortality@0

Run 7fd36b848e03 · baseline · evaluated 2026-10-29

Scores

auroc	0.936 (0.907–0.960)
auprc	0.116 (0.072–0.185)
n	29178
tokens (in / out)	0 / 0
cost (USD)	0.0000

Reuse this result

Download per-item predictions (parquet) · JSON

@misc{medbench_7fd36b848e03,
  title = {Logistic regression, mean imputation (INSPIRE authors' script) on 30-day postoperative in-hospital mortality (inspire-mortality@0)},
  author = {{medbench.kr}},
  year = {2026},
  howpublished = {\url{https://medbench.kr/r/7fd36b848e03}},
  note = {Evaluated 2026-10-29, harness p0.1, run key e580ff405f23}
}

Versions

model	`medbench/inspire-logreg` (medbench.kr)
task spec hash	`b511ba3780ec4a3391372483053ab1ad4c6afdb50968cb9cf3ef0cf4dfa383e8`
harness	`p0.1`
run key	`e580ff405f231eff764a55edec6e91698ebd25740aa3d716c0526145818311ec`
config	`{"data_hash": "66de4aacf47eda2db6327572ddfd7d3d9dfc8b3b2cd654d3a70b1d05d772c54b", "eval_split": "test", "params": {"imputer": "SimpleImputer(mean)", "max_iter": 5000}, "train_split": "train", "versions": {"scikit-learn": "1.9.1"}}`

Data

INSPIRE, CC BY 4.0.

Lim L, Lee H, Jung CW, Sim D, Borrat X, Pollard TJ, Celi LA, Mark RG, Vistisen ST, Lee HC. INSPIRE, a publicly available research dataset for perioperative medicine. Sci Data. 2024;11:655. doi:10.1038/s41597-024-03517-4. Data: INSPIRE version 1.3, doi:10.13026/4evs-wq50