Transformers and large language models are efficient feature extractors for electronic health record studies
Summary
Transformers and large language models are efficient feature extractors for electronic health record studies is a scholarly article[1].
Key Facts
Transformers and large language models are efficient feature extractors for electronic health record studies's instance of is recorded as scholarly article[2].
References
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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.
APA4ort.xyz Knowledge Graph. (2026). Transformers and large language models are efficient feature extractors for electronic health record studies. Retrieved May 24, 2026, from https://4ort.xyz/entity/transformers-and-large-language-models-are-efficient-feature-extractors-for-electronic-health-record-studies
MLA“Transformers and large language models are efficient feature extractors for electronic health record studies.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/transformers-and-large-language-models-are-efficient-feature-extractors-for-electronic-health-record-studies.
BibTeX@misc{4ortxyz_transformers-and-large-language-models-are-efficient-feature-extractors-for-electronic-health-record-studies_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Transformers and large language models are efficient feature extractors for electronic health record studies}}, year = {2026}, url = {https://4ort.xyz/entity/transformers-and-large-language-models-are-efficient-feature-extractors-for-electronic-health-record-studies}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Transformers and large language models are efficient feature extractors for electronic health record studies — https://4ort.xyz/entity/transformers-and-large-language-models-are-efficient-feature-extractors-for-electronic-health-record-studies (retrieved 2026-05-24)
