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Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes
Research article (JMIR Medical Informatics, 2021) · cited 31× · AI/ML
Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes
Summary
Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes is a scholarly article[1].
Key Facts
Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes. Retrieved May 24, 2026, from https://4ort.xyz/entity/strategies-to-address-the-lack-of-labeled-data-for-supervised-machine-learning-training-with-electronic-health-records-c
MLA“Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/strategies-to-address-the-lack-of-labeled-data-for-supervised-machine-learning-training-with-electronic-health-records-c.
BibTeX@misc{4ortxyz_strategies-to-address-the-lack-of-labeled-data-for-supervised-machine-learning-training-with-electronic-health-records-c_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes}}, year = {2026}, url = {https://4ort.xyz/entity/strategies-to-address-the-lack-of-labeled-data-for-supervised-machine-learning-training-with-electronic-health-records-c}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes — https://4ort.xyz/entity/strategies-to-address-the-lack-of-labeled-data-for-supervised-machine-learning-training-with-electronic-health-records-c (retrieved 2026-05-24)
