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pro vyhledávání: '"Le, Thanh P."'
Fine-tuning Large Language Models (LLMs) for clinical Natural Language Processing (NLP) poses significant challenges due to the domain gap and limited data availability. This study investigates the effectiveness of various adapter techniques, equival
Externí odkaz:
http://arxiv.org/abs/2407.19299
Remote patient monitoring has emerged as a prominent non-invasive method, using digital technologies and computer vision (CV) to replace traditional invasive monitoring. While neonatal and pediatric departments embrace this approach, Pediatric Intens
Externí odkaz:
http://arxiv.org/abs/2407.13341
Autor:
Luong, Tinh Son, Le, Thanh-Thien, Doan, Thang Viet, Van, Linh Ngo, Nguyen, Thien Huu, Nguyen, Diep Thi-Ngoc
Existing toxic detection models face significant limitations, such as lack of transparency, customization, and reproducibility. These challenges stem from the closed-source nature of their training data and the paucity of explanations for their evalu
Externí odkaz:
http://arxiv.org/abs/2406.14835
Autor:
Lompo, Boammani Aser, Le, Thanh-Dung
This research aims to classify numerical values extracted from medical documents across seven distinct physiological categories, employing CamemBERT-bio. Previous studies suggested that transformer-based models might not perform as well as traditiona
Externí odkaz:
http://arxiv.org/abs/2405.18448
Autor:
Le, Thanh-Dung
This study delves into the effectiveness of various learning methods in improving Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN-Transformer) in the context of pediatric intensive care units (PICU) with limit
Externí odkaz:
http://arxiv.org/abs/2405.16177
Large language models (LLMs) have become integral to our professional workflows and daily lives. Nevertheless, these machine companions of ours have a critical flaw: the huge amount of data which endows them with vast and diverse knowledge, also expo
Externí odkaz:
http://arxiv.org/abs/2405.10659
Non-native English speakers (NNESs) often face challenges in achieving fluency in their written English. AI paraphrasing tools have the potential to improve their writing by suggesting more fluent paraphrases to their original sentences. Yet, the eff
Externí odkaz:
http://arxiv.org/abs/2405.07475
Autor:
Lu, Emilie, Le, Thanh-Dung
Vital signs have been essential clinical measures. Among these, body temperature (BT) and heart rate (HR) are particularly significant, and numerous studies explored their association in hospitalized adults and children. However, a lack of in-depth r
Externí odkaz:
http://arxiv.org/abs/2405.00180
In this article, we address the challenges of image super-resolution and noise reduction, which are crucial for enhancing the quality of images derived from low-resolution or noisy data. We compared and assessed several approaches for upgrading low-r
Externí odkaz:
http://arxiv.org/abs/2404.09817
Autor:
Lompo, Boammani Aser, Le, Thanh-Dung
Medical records created by healthcare professionals upon patient admission are rich in details critical for diagnosis. Yet, their potential is not fully realized because of obstacles such as complex medical language, inadequate comprehension of medic
Externí odkaz:
http://arxiv.org/abs/2404.10171