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Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation
Research article (Frontiers in Neurology, 2023) · cited 28× · AI/ML
Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation
Summary
Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation is a scholarly article[1].
Key Facts
Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation. Retrieved May 24, 2026, from https://4ort.xyz/entity/interpretable-machine-learning-for-predicting-28-day-all-cause-in-hospital-mortality-for-hypertensive-ischemic-or-hemorr
MLA“Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/interpretable-machine-learning-for-predicting-28-day-all-cause-in-hospital-mortality-for-hypertensive-ischemic-or-hemorr.
BibTeX@misc{4ortxyz_interpretable-machine-learning-for-predicting-28-day-all-cause-in-hospital-mortality-for-hypertensive-ischemic-or-hemorr_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation}}, year = {2026}, url = {https://4ort.xyz/entity/interpretable-machine-learning-for-predicting-28-day-all-cause-in-hospital-mortality-for-hypertensive-ischemic-or-hemorr}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation — https://4ort.xyz/entity/interpretable-machine-learning-for-predicting-28-day-all-cause-in-hospital-mortality-for-hypertensive-ischemic-or-hemorr (retrieved 2026-05-24)