Qingyu Chen

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	Wszystkie	Od 2020
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i10-indeks	62	60

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65 artykułów

3 artykuły

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Zhiyong LuSenior Investigator, NLM; Adjunct Professor of CS, UIUCZweryfikowany adres z nih.gov
Tiarnan D. L. KeenanStaff Clinician, National Eye Institute, National Institutes of HealthZweryfikowany adres z nih.gov
Emily ChewNational Eye Institute/National Institutes of HealthZweryfikowany adres z nei.nih.gov
Yifan PengAssociate Professor at Weill Cornell MedicineZweryfikowany adres z med.cornell.edu
Yan HuUniversity of Texas Health Science Center at HoustonZweryfikowany adres z uth.tmc.edu
Qiao Jin, MDNational Institutes of HealthZweryfikowany adres z nih.gov
Wai T WongTiresias Biopharma ConsultingZweryfikowany adres z Tiresiasbio.com
Chih Hsuan WeiStaff Scientist, NCBI (National Center for Biotechnology Information) / NLM / NIHZweryfikowany adres z ncbi.nlm.nih.gov
Xueqing PengYale UniversityZweryfikowany adres z yale.edu
Vipina K. KelothYale UniversityZweryfikowany adres z yale.edu
Karin VerspoorExecutive Dean, School of Computing Technologies, RMIT UniversityZweryfikowany adres z rmit.edu.au
Robert LeamanStaff Scientist, NCBI/NLM/NIHZweryfikowany adres z nih.gov
Jingcheng Du, Ph.D.School of Biomedical Informatics, UTHealthZweryfikowany adres z uth.tmc.edu
Justin ZobelComputing and Information Systems, University of MelbourneZweryfikowany adres z unimelb.edu.au
Po-Ting LaiNational Center for Biotechnology Information (NCBI)Zweryfikowany adres z ncbi.nlm.nih.gov
Sun KimAmazon Alexa AI; National Center for Biotechnology Information (NCBI)Zweryfikowany adres z amazon.com
Rezarta IslamajNational Library of Medicine, National Institutes ofZweryfikowany adres z nih.gov
Lana YeganovaScientist, National Institutes of HealthZweryfikowany adres z mail.nih.gov
Hua XuRobert T. McCluskey Professor, Section of Biomedical Informatics and Data Science, Yale UniversityZweryfikowany adres z yale.edu
Shubo TIANNCBIZweryfikowany adres z nih.gov

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Qingyu Chen

Biomedical Informatics & Data Science, Yale University; NCBI-NLM, National Institutes of Health

Zweryfikowany adres z yale.edu - Strona główna

Text mining Machine learning Data curation BioNLP Medical Imaging Analysis


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
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	497	2019
Keep up with the latest coronavirus research Q Chen, A Allot, Z Lu Nature 579 (7798), 193-193, 2020	333	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	331	2019
LitCovid: an open database of COVID-19 literature Q Chen, A Allot, Z Lu Nucleic acids research 49 (D1), D1534-D1540, 2021	314	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	221	2019
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	210	2024
Improving large language models for clinical named entity recognition via prompt engineering Y Hu, Q Chen, J Du, X Peng, VK Keloth, X Zuo, Y Zhou, Z Li, X Jiang, Z Lu, ... Journal of the American Medical Informatics Association, ocad259, 2024	201*	2024
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	172	2019
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	116	2024
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	116	2020
MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval Q Jin, W Kim, Q Chen, DC Comeau, L Yeganova, WJ Wilbur, Z Lu Bioinformatics 39 (11), btad651, 2023	85	2023
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	75	2021
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	73	2022
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	71	2019
Biocuration: distilling data into knowledge International Society for Biocuration PLoS Biology 16 (4), e2002846, 2018	63	2018
Large language models in biomedical natural language processing: benchmarks, baselines, and recommendations Q Chen, J Du, Y Hu, VK Keloth, X Peng, K Raja, R Zhang, Z Lu, H Xu arXiv preprint arXiv:2305.16326, 2023	60*	2023
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	60	2020
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	60	2019
LitSuggest: a web-based system for literature recommendation and curation using machine learning A Allot, K Lee, Q Chen, L Luo, Z Lu Nucleic acids research 49 (W1), W352-W358, 2021	58	2021
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	57	2019

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