Qingyu Chen
Qingyu Chen
Biomedical Informatics & Data Science, Yale University; NCBI-NLM, National Institutes of Health
Verified email at - Homepage
Cited by
Cited by
BioWordVec, improving biomedical word embeddings with subword information and MeSH
Y Zhang, Q Chen, Z Yang, H Lin, Z Lu
Scientific data 6 (1), 52, 2019
Keep up with the latest coronavirus research
Q Chen, A Allot, Z Lu
Nature 579 (7798), 193-193, 2020
DeepSeeNet: a deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographs
Y Peng, S Dharssi, Q Chen, TD Keenan, E Agrón, WT Wong, EY Chew, ...
Ophthalmology 126 (4), 565-575, 2019
LitCovid: an open database of COVID-19 literature
Q Chen, A Allot, Z Lu
Nucleic acids research 49 (D1), D1534-D1540, 2021
BioSentVec: creating sentence embeddings for biomedical texts
Q Chen, Y Peng, Z Lu
2019 IEEE International Conference on Healthcare Informatics (ICHI), 1-5, 2019
ML-Net: multi-label classification of biomedical texts with deep neural networks
J Du, Q Chen, Y Peng, Y Xiang, C Tao, Z Lu
Journal of the American Medical Informatics Association 26 (11), 1279-1285, 2019
An empirical study of multi-task learning on BERT for biomedical text mining
Y Peng, Q Chen, Z Lu
arXiv preprint arXiv:2005.02799, 2020
Opportunities and challenges for ChatGPT and large language models in biomedicine and health
S Tian, Q Jin, L Yeganova, PT Lai, Q Zhu, X Chen, Y Yang, Q Chen, ...
Briefings in Bioinformatics 25 (1), bbad493, 2024
Artificial intelligence in action: addressing the COVID-19 pandemic with natural language processing
Q Chen, R Leaman, A Allot, L Luo, CH Wei, S Yan, Z Lu
Annual review of biomedical data science 4 (1), 313-339, 2021
Genegpt: Augmenting large language models with domain tools for improved access to biomedical information
Q Jin, Y Yang, Q Chen, Z Lu
Bioinformatics 40 (2), btae075, 2024
A deep learning approach for automated detection of geographic atrophy from color fundus photographs
TD Keenan, S Dharssi, Y Peng, Q Chen, E Agrón, WT Wong, Z Lu, ...
Ophthalmology 126 (11), 1533-1540, 2019
Biocuration: distilling data into knowledge
International Society for Biocuration
PLoS Biology 16 (4), e2002846, 2018
Duplicates, redundancies and inconsistencies in the primary nucleotide databases: a descriptive study
Q Chen, J Zobel, K Verspoor
Database 2017, baw163, 2017
Predicting myocardial infarction through retinal scans and minimal personal information
A Diaz-Pinto, N Ravikumar, R Attar, A Suinesiaputra, Y Zhao, E Levelt, ...
Nature Machine Intelligence 4 (1), 55-61, 2022
LitSense: making sense of biomedical literature at sentence level
A Allot, Q Chen, S Kim, R Vera Alvarez, DC Comeau, WJ Wilbur, Z Lu
Nucleic acids research 47 (W1), W594-W599, 2019
A multi-task deep learning model for the classification of Age-related Macular Degeneration
Q Chen, Y Peng, T Keenan, S Dharssi, E Agro, W Wai, E Chew, Z Lu
AMIA Summits on Translational Science Proceedings 2019, 505, 2019
BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale
Q Chen, K Lee, S Yan, S Kim, CH Wei, Z Lu
PLoS computational biology 16 (4), e1007617, 2020
Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine
R Islamaj Doğan, S Kim, A Chatr-Aryamontri, CH Wei, DC Comeau, ...
Database 2019, bay147, 2019
Predicting risk of late age-related macular degeneration using deep learning
Y Peng, TD Keenan, Q Chen, E Agrón, A Allot, WT Wong, EY Chew, Z Lu
NPJ digital medicine 3 (1), 111, 2020
Integrating bdi agents into a matsim simulation
L Padgham, K Nagel, D Singh, Q Chen
ECAI 2014, 681-686, 2014
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