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Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes
Research article (Natural Language Processing Journal, 2023) · cited 11× · AI/ML
Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes
Summary
Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes is a scholarly article[1].
Key Facts
Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes'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). Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes. Retrieved May 24, 2026, from https://4ort.xyz/entity/enhancing-pre-trained-contextual-embeddings-with-triplet-loss-as-an-effective-fine-tuning-method-for-extracting-clinical
MLA“Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/enhancing-pre-trained-contextual-embeddings-with-triplet-loss-as-an-effective-fine-tuning-method-for-extracting-clinical.
BibTeX@misc{4ortxyz_enhancing-pre-trained-contextual-embeddings-with-triplet-loss-as-an-effective-fine-tuning-method-for-extracting-clinical_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes}}, year = {2026}, url = {https://4ort.xyz/entity/enhancing-pre-trained-contextual-embeddings-with-triplet-loss-as-an-effective-fine-tuning-method-for-extracting-clinical}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Enhancing pre-trained contextual embeddings with triplet loss as an effective fine-tuning method for extracting clinical features from electronic health record derived mental health clinical notes — https://4ort.xyz/entity/enhancing-pre-trained-contextual-embeddings-with-triplet-loss-as-an-effective-fine-tuning-method-for-extracting-clinical (retrieved 2026-05-24)
