Results 31 to 40 of about 3,266 (219)
Biomedical Flat and Nested Named Entity Recognition: Methods, Challenges, and Advances
Applied SciencesBiomedical named entity recognition (BioNER) aims to identify and classify biomedical entities (i.e., diseases, chemicals, and genes) from text into predefined classes. This process serves as an important initial step in extracting biomedical information
Yesol Park, Gyujin Son, Mina Rho
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BMC Medical Informatics and Decision Making, 2019 Background This paper presents a conditional random fields (CRF) method that enables the capture of specific high-order label transition factors to improve clinical named entity recognition performance.
Wangjin Lee, Jinwook Choi
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MULTITHREAD IN NAMED ENTITY RECOGNITION [PDF]
International Journal of Intelligent Computing and Information Sciences, 2016 According to Gordon Earle Moore, Every two years, the number of core on a CPU chip is doubling. So we change our program to use threads for different reasons, program will run faster and make better use of the multiple CPU/core architecture that you are ...
Z. Rabea, M. Abu Elsoud, M. Rashed
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Domain Specific Entity Recognition With Semantic-Based Deep Learning Approach
IEEE Access, 2021 In digital agriculture, agronomists are required to make timely, profitable and more actionable precise decisions based on knowledge and experience. The input can be cultivated and related agricultural data, and one of them is text data, including news ...
Quoc Hung Ngo +2 more
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An Improved Approach to the Construction of Chinese Medical Knowledge Graph Based on CTD-BLSTM Model
IEEE Access, 2021 In the process of constructing the knowledge graph, entity recognition and relationship extraction are not only the most fundamental but also the most important tasks, and the effect of their model directly affects the final result of the graph.
Yang Wu, Xiyong Zhu, Yinan Zhu
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OWNER — Toward Unsupervised Open-World Named Entity Recognition
IEEE AccessNamed Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP), traditionally addressed through supervised learning, which requires extensive annotated corpora. This requirement poses challenges, particularly in specialized domains
Pierre-Yves Genest +3 more
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A Research Toward Chinese Named Entity Recognition Based on Transfer Learning
International Journal of Computational Intelligence Systems, 2023 To improve the performance of named entity recognition in the lack of well-annotated entity data, a transfer learning-based Chinese named entity recognition model is proposed in this paper.
Hui Kang +5 more
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MAF-CNER : A Chinese Named Entity Recognition Model Based on Multifeature Adaptive Fusion
Complexity, 2021 Named entity recognition (NER) is a subtask in natural language processing, and its accuracy greatly affects the effectiveness of downstream tasks. Aiming at the problem of insufficient expression of potential Chinese features in named entity recognition
Xuming Han +5 more
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Multi-grained Named Entity Recognition [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 In ACL 2019 as a long ...
Congying Xia +8 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source