[HTML][HTML] Chinese named entity recognition: The state of the art
Abstract Named Entity Recognition (NER), one of the most fundamental problems in natural
language processing, seeks to identify the boundaries and types of entities with specific …
language processing, seeks to identify the boundaries and types of entities with specific …
Deep learning in clinical natural language processing: a methodical review
Objective This article methodically reviews the literature on deep learning (DL) for natural
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
Chinese clinical named entity recognition via multi-head self-attention based BiLSTM-CRF
Clinical named entity recognition (CNER) is a fundamental step for many clinical Natural
Language Processing (NLP) systems, which aims to recognize and classify clinical entities …
Language Processing (NLP) systems, which aims to recognize and classify clinical entities …
An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records
L Li, J Zhao, L Hou, Y Zhai, J Shi, F Cui - BMC Medical Informatics and …, 2019 - Springer
Background Clinical named entity recognition (CNER) is important for medical information
mining and establishment of high-quality knowledge map. Due to the different text features …
mining and establishment of high-quality knowledge map. Due to the different text features …
Review of attention mechanism in natural language processing
S Lei, W Yi, C Ying, W Ruibin - Data Analysis and …, 2020 - manu44.magtech.com.cn
[Objective] This paper summarizes the evolution and application of attention mechanism in
natural language processing.[Coverage] We searched “attention” with the title/topic fields of …
natural language processing.[Coverage] We searched “attention” with the title/topic fields of …
A deep language model for symptom extraction from clinical text and its application to extract COVID-19 symptoms from social media
Patients experience various symptoms when they haveeither acute or chronic diseases or
undergo some treatments for diseases. Symptoms are often indicators of the severity of the …
undergo some treatments for diseases. Symptoms are often indicators of the severity of the …
Higher education programming competencies: a novel dataset
N Kiesler, B Pfülb - International Conference on Artificial Neural Networks, 2023 - Springer
Students' challenges in introductory programming courses have long been subject to
research. In fact, learners are faced with cognitively complex tasks, such as modeling and …
research. In fact, learners are faced with cognitively complex tasks, such as modeling and …
Invariant signature, logic reasoning, and semantic natural language processing (NLP)-based automated building code compliance checking (I-SNACC) framework
Traditional manual building code compliance checking is costly, time-consuming, and
human error-prone. With the adoption of Building Information Modeling (BIM), automation in …
human error-prone. With the adoption of Building Information Modeling (BIM), automation in …
Theoretical understanding of deep learning in uav biomedical engineering technologies analysis
The unmanned aerial vehicles (UAVs) emerged into a promising research trend within the
recurrent year where current and future networks are to use enhanced connectivity in these …
recurrent year where current and future networks are to use enhanced connectivity in these …
A 5g beam selection machine learning algorithm for unmanned aerial vehicle applications
The unmanned aerial vehicles (UAVs) emerged into a promising research trend within the
recurrent year where current and future networks are to use enhanced connectivity in these …
recurrent year where current and future networks are to use enhanced connectivity in these …