Zobrazeno 1 - 10
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pro vyhledávání: '"A. Bernal-Jiménez"'
Publikováno v:
Psicosomática y Psiquiatría, Iss 28 (2024)
Resumen: (1) Introducción: La enfermedad por COVID-19 ha afectado a millones de personas en todo el mundo y ha planteado un desafío sin precedentes a los sistemas de salud, provocando medidas como el distanciamiento social y el confinamiento domici
Externí odkaz:
https://doaj.org/article/4ef7d0adb05f4f08bf0197724d2f1958
In order to thrive in hostile and ever-changing natural environments, mammalian brains evolved to store large amounts of knowledge about the world and continually integrate new information while avoiding catastrophic forgetting. Despite the impressiv
Externí odkaz:
http://arxiv.org/abs/2405.14831
As opposed to general English, many concepts in biomedical terminology have been designed in recent history by biomedical professionals with the goal of being precise and concise. This is often achieved by concatenating meaningful biomedical morpheme
Externí odkaz:
http://arxiv.org/abs/2306.17649
Recent work has shown that fine-tuning large language models (LLMs) on large-scale instruction-following datasets substantially improves their performance on a wide range of NLP tasks, especially in the zero-shot setting. However, even advanced instr
Externí odkaz:
http://arxiv.org/abs/2305.11159
Autor:
Gutiérrez, Bernal Jiménez, McNeal, Nikolas, Washington, Clay, Chen, You, Li, Lang, Sun, Huan, Su, Yu
The strong few-shot in-context learning capability of large pre-trained language models (PLMs) such as GPT-3 is highly appealing for application domains such as biomedicine, which feature high and diverse demands of language technologies but also hig
Externí odkaz:
http://arxiv.org/abs/2203.08410
The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields. We provide an analysis of several multi-label document clas
Externí odkaz:
http://arxiv.org/abs/2006.13816
Machine reading comprehension has made great progress in recent years owing to large-scale annotated datasets. In the clinical domain, however, creating such datasets is quite difficult due to the domain expertise required for annotation. Recently, P
Externí odkaz:
http://arxiv.org/abs/2005.00574
Akademický článek
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Akademický článek
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Autor:
Manzano-Felipe, María Ángeles, Cruz-Cobo, Celia, Bernal-Jiménez, María Ángeles, Santi-Cano, María José
Publikováno v:
Journal of Research in Nursing; Aug2024, Vol. 29 Issue 4/5, p348-363, 16p