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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
Wonjin Yoon, Chan Ho So, Jinhyuk Lee, et al.
BMC Bioinformatics (2019) Vol. 20, Iss. S10
Open Access | Times Cited: 105

Showing 1-25 of 105 citing articles:

BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, et al.
Bioinformatics (2019) Vol. 36, Iss. 4, pp. 1234-1240
Open Access | Times Cited: 5128
SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, Arman Cohan
(2019)
Open Access | Times Cited: 2401
Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets
Yifan Peng, Shankai Yan, Zhiyong Lu
(2019)
Open Access | Times Cited: 723
Building a PubMed knowledge graph
Jian Xu, Sunkyu Kim, Min Song, et al.
Scientific Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 149
Enriching contextualized language model from knowledge graph for biomedical information extraction
Fei Hao, Yafeng Ren, Yue Zhang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 141
Pretrained Language Models for Biomedical and Clinical Tasks: Understanding and Extending the State-of-the-Art
Patrick Lewis, Myle Ott, Jingfei Du, et al.
(2020)
Open Access | Times Cited: 138
Named Entity Recognition and Relation Detection for Biomedical Information Extraction
Nadeesha Perera, Matthias Dehmer, Frank Emmert‐Streib
Frontiers in Cell and Developmental Biology (2020) Vol. 8
Open Access | Times Cited: 128
A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining
Donghyeon Kim, Jinhyuk Lee, Chan Ho So, et al.
IEEE Access (2019) Vol. 7, pp. 73729-73740
Open Access | Times Cited: 125
Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition
Minsoo Cho, Jihwan Ha, Chihyun Park, et al.
Journal of Biomedical Informatics (2020) Vol. 103, pp. 103381-103381
Closed Access | Times Cited: 100
Biomedical named entity recognition using BERT in the machine reading comprehension framework
Cong Sun, Zhihao Yang, Lei Wang, et al.
Journal of Biomedical Informatics (2021) Vol. 118, pp. 103799-103799
Open Access | Times Cited: 98
HunFlair: an easy-to-use tool for state-of-the-art biomedical named entity recognition
Leon Weber, Mario Sänger, Jannes Münchmeyer, et al.
Bioinformatics (2021) Vol. 37, Iss. 17, pp. 2792-2794
Open Access | Times Cited: 87
Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison
Bosheng Song, Fen Li, Yuansheng Liu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 85
A comparative study of pretrained language models for long clinical text
Yikuan Li, Ramsey M. Wehbe, Faraz S. Ahmad, et al.
Journal of the American Medical Informatics Association (2022) Vol. 30, Iss. 2, pp. 340-347
Open Access | Times Cited: 68
Pre-trained Language Model for Biomedical Question Answering
Wonjin Yoon, Jinhyuk Lee, Donghyeon Kim, et al.
Communications in computer and information science (2020), pp. 727-740
Closed Access | Times Cited: 67
BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition
Usman Naseem, Matloob Khushi, V. Lakshma Reddy, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2021), pp. 1-7
Open Access | Times Cited: 46
Hierarchical shared transfer learning for biomedical named entity recognition
Zhaoying Chai, Jin Han, Shenghui Shi, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 35
Constructing a disease database and using natural language processing to capture and standardize free text clinical information
Shaina Raza, Brian Schwartz
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 22
Extraction of knowledge graph of Covid-19 through mining of unstructured biomedical corpora
Sudhakaran Gajendran, D. Manjula, Vijayan Sugumaran, et al.
Computational Biology and Chemistry (2023) Vol. 102, pp. 107808-107808
Open Access | Times Cited: 18
Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach
Shaina Raza, Brian Schwartz
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 18
SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, Arman Cohan
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 50
Character level and word level embedding with bidirectional LSTM – Dynamic recurrent neural network for biomedical named entity recognition from literature
Sudhakaran Gajendran, D. Manjula, Vijayan Sugumaran
Journal of Biomedical Informatics (2020) Vol. 112, pp. 103609-103609
Open Access | Times Cited: 49
Improving biomedical named entity recognition with syntactic information
Yuanhe Tian, Shen Wang, Yan Song, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 42
Biomedical Named-Entity Recognition by Hierarchically Fusing BioBERT Representations and Deep Contextual-Level Word-Embedding
Usman Naseem, Katarzyna Musiał, Peter Eklund, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2020), pp. 1-8
Open Access | Times Cited: 40
Multi-attention deep neural network fusing character and word embedding for clinical and biomedical concept extraction
Shengyu Fan, Hui Yu, Xiaoya Cai, et al.
Information Sciences (2022) Vol. 608, pp. 778-793
Closed Access | Times Cited: 24
COVIDScholar: An automated COVID-19 research aggregation and analysis platform
John Dagdelen, Amalie Trewartha, Haoyan Huo, et al.
PLoS ONE (2023) Vol. 18, Iss. 2, pp. e0281147-e0281147
Open Access | Times Cited: 13
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