Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth
Summary
Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth is a scholarly article[1].
Key Facts
Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth. Retrieved May 24, 2026, from https://4ort.xyz/entity/dense-phenotyping-from-electronic-health-records-enables-machine-learning-based-prediction-of-preterm-birth
MLA“Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dense-phenotyping-from-electronic-health-records-enables-machine-learning-based-prediction-of-preterm-birth.
BibTeX@misc{4ortxyz_dense-phenotyping-from-electronic-health-records-enables-machine-learning-based-prediction-of-preterm-birth_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth}}, year = {2026}, url = {https://4ort.xyz/entity/dense-phenotyping-from-electronic-health-records-enables-machine-learning-based-prediction-of-preterm-birth}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Dense phenotyping from electronic health records enables machine learning-based prediction of preterm birth — https://4ort.xyz/entity/dense-phenotyping-from-electronic-health-records-enables-machine-learning-based-prediction-of-preterm-birth (retrieved 2026-05-24)
