Zobrazeno 1 - 10
of 817
pro vyhledávání: '"Han, Lifeng"'
Autor:
Li, Zihao, Belkadi, Samuel, Micheletti, Nicolo, Han, Lifeng, Shardlow, Matthew, Nenadic, Goran
In this system report, we describe the models and methods we used for our participation in the PLABA2023 task on biomedical abstract simplification, part of the TAC 2023 tracks. The system outputs we submitted come from the following three categories
Externí odkaz:
http://arxiv.org/abs/2408.03871
This study aims to explore the implementation of Natural Language Processing (NLP) and machine learning (ML) techniques to automate the coding of medical letters with visualised explainability and light-weighted local computer settings. Currently in
Externí odkaz:
http://arxiv.org/abs/2407.13638
Autor:
Lommel, Arle, Gladkoff, Serge, Melby, Alan, Wright, Sue Ellen, Strandvik, Ingemar, Gasova, Katerina, Vaasa, Angelika, Benzo, Andy, Sparano, Romina Marazzato, Foresi, Monica, Innis, Johani, Han, Lifeng, Nenadic, Goran
The year 2024 marks the 10th anniversary of the Multidimensional Quality Metrics (MQM) framework for analytic translation quality evaluation. The MQM error typology has been widely used by practitioners in the translation and localization industry an
Externí odkaz:
http://arxiv.org/abs/2405.16969
Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this field. However, the prevalent approach used in text generation, Causal La
Externí odkaz:
http://arxiv.org/abs/2405.12630
This paper investigates the development and evaluation of machine translation models from Cantonese to English, where we propose a novel approach to tackle low-resource language translations. The main objectives of the study are to develop a model th
Externí odkaz:
http://arxiv.org/abs/2405.08172
Neural Machine Translation (NMT) for low-resource languages is still a challenging task in front of NLP researchers. In this work, we deploy a standard data augmentation methodology by back-translation to a new language translation direction Cantones
Externí odkaz:
http://arxiv.org/abs/2403.11346
We conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. Furthermore, to address the language resource imbalance issue, we also carry out
Externí odkaz:
http://arxiv.org/abs/2312.07250
Access to real-world medication prescriptions is essential for medical research and healthcare quality improvement. However, access to real medication prescriptions is often limited due to the sensitive nature of the information expressed. Additional
Externí odkaz:
http://arxiv.org/abs/2310.19727
Clinical texts, represented in electronic medical records (EMRs), contain rich medical information and are essential for disease prediction, personalised information recommendation, clinical decision support, and medication pattern mining and measure
Externí odkaz:
http://arxiv.org/abs/2310.02229
Autor:
Li, Zihao, Belkadi, Samuel, Micheletti, Nicolo, Han, Lifeng, Shardlow, Matthew, Nenadic, Goran
Biomedical literature often uses complex language and inaccessible professional terminologies. That is why simplification plays an important role in improving public health literacy. Applying Natural Language Processing (NLP) models to automate such
Externí odkaz:
http://arxiv.org/abs/2309.13202