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Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study
Research article (PLOS Digital Health, 2024) · cited 16× · AI/ML
Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study
Summary
Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study is a scholarly article[1].
Key Facts
Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study. Retrieved May 24, 2026, from https://4ort.xyz/entity/comparison-of-machine-learning-and-logistic-regression-models-for-prediction-of-30-day-unplanned-readmission-in-electron
MLA“Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comparison-of-machine-learning-and-logistic-regression-models-for-prediction-of-30-day-unplanned-readmission-in-electron.
BibTeX@misc{4ortxyz_comparison-of-machine-learning-and-logistic-regression-models-for-prediction-of-30-day-unplanned-readmission-in-electron_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study}}, year = {2026}, url = {https://4ort.xyz/entity/comparison-of-machine-learning-and-logistic-regression-models-for-prediction-of-30-day-unplanned-readmission-in-electron}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Comparison of machine-learning and logistic regression models for prediction of 30-day unplanned readmission in electronic health records: A development and validation study — https://4ort.xyz/entity/comparison-of-machine-learning-and-logistic-regression-models-for-prediction-of-30-day-unplanned-readmission-in-electron (retrieved 2026-05-24)
