Home › Entities › academia › Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study

Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study

Research article (Journal of Psychosomatic Research, 2023) · cited 17× · AI/ML
academia openalex:W4388816393
Press Enter · cited answer in seconds

Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study

Summary

Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study is a scholarly article[1].

Key Facts

  • Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

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.

APA 4ort.xyz Knowledge Graph. (2026). Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study. Retrieved May 24, 2026, from https://4ort.xyz/entity/online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by
MLA “Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by.
BibTeX @misc{4ortxyz_online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study}}, year = {2026}, url = {https://4ort.xyz/entity/online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study — https://4ort.xyz/entity/online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/online-interpretable-dynamic-prediction-models-for-postoperative-delirium-after-cardiac-surgery-under-cardiopulmonary-by · Last refreshed: