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Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study
Research article (Journal of Diabetes Research, 2020) · cited 117× · AI/ML
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study
Summary
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study is a scholarly article[1].
Key Facts
Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study. Retrieved May 24, 2026, from https://4ort.xyz/entity/comparison-of-machine-learning-methods-and-conventional-logistic-regressions-for-predicting-gestational-diabetes-using-r
MLA“Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/comparison-of-machine-learning-methods-and-conventional-logistic-regressions-for-predicting-gestational-diabetes-using-r.
BibTeX@misc{4ortxyz_comparison-of-machine-learning-methods-and-conventional-logistic-regressions-for-predicting-gestational-diabetes-using-r_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Comparison of Machine Learning Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study}}, year = {2026}, url = {https://4ort.xyz/entity/comparison-of-machine-learning-methods-and-conventional-logistic-regressions-for-predicting-gestational-diabetes-using-r}, 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 Methods and Conventional Logistic Regressions for Predicting Gestational Diabetes Using Routine Clinical Data: A Retrospective Cohort Study — https://4ort.xyz/entity/comparison-of-machine-learning-methods-and-conventional-logistic-regressions-for-predicting-gestational-diabetes-using-r (retrieved 2026-05-24)
