[HTML] jmir.org

[HTML][HTML] The impact of pretrained language models on negation and speculation detection in cross-lingual medical text: comparative study

RR Zavala, P Martinez - JMIR medical informatics, 2020 - medinform.jmir.org
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
被引用次数：28 相关文章
[PDF] researchgate.net

[PDF][PDF] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR, 2020 - researchgate.net
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[PDF] uc3m.es

[PDF][PDF] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR, 2020 - e-archivo.uc3m.es
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[PDF] academia.edu

[PDF][PDF] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR, 2020 - academia.edu
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[HTML] jmir.org

[HTML][HTML] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

R Rivera Zavala, P Martinez - JMIR Medical Informatics, 2020 - medinform.jmir.org
Background Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …

The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR medical informatics, 2020 - pubmed.ncbi.nlm.nih.gov
Background Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[PDF] archive.org

[PDF][PDF] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR, 2020 - scholar.archive.org
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[PDF] semanticscholar.org

[PDF][PDF] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR, 2020 - pdfs.semanticscholar.org
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …
[HTML] nih.gov

[HTML][HTML] The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR Medical Informatics, 2020 - ncbi.nlm.nih.gov
Background Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …

The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

RR Zavala, P Martinez - JMIR Medical Informatics, 2020 - search.proquest.com
Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …