AIMC Topic: Language

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Enhancing unsupervised medical entity linking with multi-instance learning.

BMC medical informatics and decision making
BACKGROUND: A lot of medical mentions can be extracted from a huge amount of medical texts. In order to make use of these medical mentions, a prerequisite step is to link those medical mentions to a medical domain knowledge base (KB). This linkage of...

Combining data augmentation and domain information with TENER model for Clinical Event Detection.

BMC medical informatics and decision making
BACKGROUND: In recent years, with the development of artificial intelligence, the use of deep learning technology for clinical information extraction has become a new trend. Clinical Event Detection (CED) as its subtask has attracted the attention fr...

Application of Neural Network Algorithm Based on Principal Component Image Analysis in Band Expansion of College English Listening.

Computational intelligence and neuroscience
With the development of information technology, band expansion technology is gradually applied to college English listening teaching. This technology aims to recover broadband speech signals from narrowband speech signals with a limited frequency ban...

A clinical specific BERT developed using a huge Japanese clinical text corpus.

PloS one
Generalized language models that are pre-trained with a large corpus have achieved great performance on natural language tasks. While many pre-trained transformers for English are published, few models are available for Japanese text, especially in c...

Deep Learning-Based Methods for Sentiment Analysis on Nepali COVID-19-Related Tweets.

Computational intelligence and neuroscience
COVID-19 has claimed several human lives to this date. People are dying not only because of physical infection of the virus but also because of mental illness, which is linked to people's sentiments and psychologies. People's written texts/posts scat...

Does the magic of BERT apply to medical code assignment? A quantitative study.

Computers in biology and medicine
Unsupervised pretraining is an integral part of many natural language processing systems, and transfer learning with language models has achieved remarkable results in downstream tasks. In the clinical application of medical code assignment, diagnosi...

Enriching Human-Robot Interaction with Mobile App in Interventions of Children with Autism Spectrum Disorder.

Prilozi (Makedonska akademija na naukite i umetnostite. Oddelenie za medicinski nauki)
: Autism spectrum disorder (ASD) is a group of complex lifelong neurodevelopmental disorders, characterized by difficulties in social communication and stereotyped behaviours. Due to the increasing number of children with ASD, it is important to cont...

Estimating redundancy in clinical text.

Journal of biomedical informatics
The current mode of use of Electronic Health Records (EHR) elicits text redundancy. Clinicians often populate new documents by duplicating existing notes, then updating accordingly. Data duplication can lead to propagation of errors, inconsistencies ...

Impacts of multicollinearity on CAPT modalities: An heterogeneous machine learning framework for computer-assisted French phoneme pronunciation training.

PloS one
Phoneme pronunciations are usually considered as basic skills for learning a foreign language. Practicing the pronunciations in a computer-assisted way is helpful in a self-directed or long-distance learning environment. Recent researches indicate th...

Automatic Detection of Grammatical Errors in English Verbs Based on RNN Algorithm: Auxiliary Objectives for Neural Error Detection Models.

Computational intelligence and neuroscience
With the rapid development of neural network technology, we have widely used this technology in various fields. In the field of language translation, the research on automatic detection technology of English verb grammatical errors is in a hot stage....