AIMC Topic: Language

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ParaMed: a parallel corpus for English-Chinese translation in the biomedical domain.

BMC medical informatics and decision making
BACKGROUND: Biomedical language translation requires multi-lingual fluency as well as relevant domain knowledge. Such requirements make it challenging to train qualified translators and costly to generate high-quality translations. Machine translatio...

A Review of Recent Work in Transfer Learning and Domain Adaptation for Natural Language Processing of Electronic Health Records.

Yearbook of medical informatics
OBJECTIVES: We survey recent work in biomedical NLP on building more adaptable or generalizable models, with a focus on work dealing with electronic health record (EHR) texts, to better understand recent trends in this area and identify opportunities...

Enhancing Biomedical Relation Extraction with Transformer Models using Shortest Dependency Path Features and Triplet Information.

Journal of biomedical informatics
Entity relation extraction plays an important role in the biomedical, healthcare, and clinical research areas. Recently, pre-trained models based on transformer architectures and their variants have shown remarkable performances in various natural la...

English Feature Recognition Based on GA-BP Neural Network Algorithm and Data Mining.

Computational intelligence and neuroscience
With the development of society and the promotion of science and technology, English, as the largest universal language in the world, is used by more and more people. In the life around us, there is information in English all the time. However, becau...

Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language.

International journal of environmental research and public health
Harmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven an...

Qualifying Certainty in Radiology Reports through Deep Learning-Based Natural Language Processing.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Communication gaps exist between radiologists and referring physicians in conveying diagnostic certainty. We aimed to explore deep learning-based bidirectional contextual language models for automatically assessing diagnostic ...

English Grammar Detection Based on LSTM-CRF Machine Learning Model.

Computational intelligence and neuroscience
Deep learning and neural network have been widely used in the field of speech, vocabulary, text, pictures, and other information processing fields, which has achieved excellent research results. Neural network algorithm and prediction model were used...

Creating efficiencies in the extraction of data from randomized trials: a prospective evaluation of a machine learning and text mining tool.

BMC medical research methodology
BACKGROUND: Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We evaluated a machine learning and text mining tool's ability to (a) automatically extract data elements from randomized t...

Analysis of Color Language and Aesthetic Paradigm of Print Art Based on GB-BP Neural Network.

Computational intelligence and neuroscience
Color is the basic element of printmaking art creation and also an important medium for artists to express their emotions. In order to improve the understanding of the print by tourists, the research first carries out image analysis of different colo...

Aspect-based sentiment analysis with graph convolution over syntactic dependencies.

Artificial intelligence in medicine
Aspect-based sentiment analysis is a natural language processing task whose aim is to automatically classify the sentiment associated with a specific aspect of a written text. In this study, we propose a novel model for aspect-based sentiment analysi...