David Chen

9.2k total citations · 2 hit papers
161 papers, 6.4k citations indexed

About

David Chen is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, David Chen has authored 161 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 26 papers in Radiology, Nuclear Medicine and Imaging and 21 papers in Artificial Intelligence. Recurrent topics in David Chen's work include DNA Repair Mechanisms (15 papers), Cardiac Imaging and Diagnostics (10 papers) and Topic Modeling (7 papers). David Chen is often cited by papers focused on DNA Repair Mechanisms (15 papers), Cardiac Imaging and Diagnostics (10 papers) and Topic Modeling (7 papers). David Chen collaborates with scholars based in United States, Canada and France. David Chen's co-authors include William B. Dolan, Benjamin P.C. Chen, Utz Herbig, John M. Sedivy, Gloria C. Li, Akihiro Kurimasa, Steven M. Yannone, C. S. Kang, Y. P. Chang and Sara Sarid and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

David Chen

149 papers receiving 6.2k citations

Hit Papers

Telomere Shortening Triggers Senescence of Human Cells th... 2004 2026 2011 2018 2004 2011 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Chen United States 40 3.3k 1.1k 920 583 581 161 6.4k
Hans A. Kestler Germany 45 3.4k 1.1× 578 0.5× 917 1.0× 301 0.5× 798 1.4× 264 7.2k
Chandan Chakraborty India 46 1.6k 0.5× 459 0.4× 624 0.7× 1.1k 1.9× 615 1.1× 178 7.2k
Stuart A. Cook United Kingdom 53 4.8k 1.5× 755 0.7× 541 0.6× 336 0.6× 717 1.2× 208 11.3k
Ting Chen China 43 3.0k 0.9× 261 0.2× 369 0.4× 569 1.0× 423 0.7× 374 7.1k
Yazhuo Zhang China 33 3.3k 1.0× 240 0.2× 945 1.0× 424 0.7× 926 1.6× 341 8.1k
Jean Yang Australia 52 8.2k 2.5× 1.2k 1.1× 1.4k 1.5× 202 0.3× 1.6k 2.7× 257 13.8k
Balasubramanian Narasimhan United States 30 2.4k 0.7× 229 0.2× 687 0.7× 212 0.4× 733 1.3× 67 5.5k
Sorin Drăghici United States 47 6.6k 2.0× 360 0.3× 475 0.5× 227 0.4× 1.4k 2.5× 171 10.7k
B. Herman United States 35 2.6k 0.8× 528 0.5× 573 0.6× 102 0.2× 299 0.5× 73 5.7k
Christine Decaestecker Belgium 52 3.5k 1.1× 212 0.2× 1.6k 1.8× 372 0.6× 937 1.6× 287 8.7k

Countries citing papers authored by David Chen

Since Specialization
Citations

This map shows the geographic impact of David Chen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Chen more than expected).

Fields of papers citing papers by David Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Chen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Chen. The network helps show where David Chen may publish in the future.

Co-authorship network of co-authors of David Chen

This figure shows the co-authorship network connecting the top 25 collaborators of David Chen. A scholar is included among the top collaborators of David Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Chen. David Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Chen, Chun, et al.. (2025). Cost and supply considerations for antibody therapeutics. mAbs. 17(1). 2451789–2451789. 15 indexed citations
3.
Huang, Ryan S., David Chen, Andrew Mihalache, et al.. (2025). Patient-Reported Outcomes as Prognostic Indicators for Overall Survival in Cancer. JAMA Oncology. 11(11). 1303–1303.
4.
Liu, Yuchi, David E. Sosnovik, Mazen Hanna, et al.. (2025). Free‐Breathing Multi‐Slice Co‐Registered Cardiac T1 , T2 , and ADC Mapping With Spin‐Echo Echo Planar Imaging. Magnetic Resonance in Medicine. 95(4). 2035–2051.
5.
Chen, David, et al.. (2024). Review of brachytherapy clinical trials: a cross-sectional analysis of ClinicalTrials.gov. Radiation Oncology. 19(1). 22–22. 4 indexed citations
6.
Wang, Tom Kai Ming, Nancy A. Obuchowski, Zoran Popović, et al.. (2024). Impact of Cardiac Magnetic Resonance Left Atrial Ejection Fraction in Advanced Ischemic Cardiomyopathy. JACC Advances. 3(2). 100796–100796. 1 indexed citations
7.
Kwon, Deborah, Tom Kai Ming Wang, Samir Kapadia, et al.. (2024). Cardiac MRI-Enriched Phenomapping Classification and Differential Treatment Outcomes in Patients With Ischemic Cardiomyopathy. Circulation Cardiovascular Imaging. 17(4). e016006–e016006. 3 indexed citations
8.
Kapadia, Samir, Lars G. Svensson, Richard A. Grimm, et al.. (2024). Leveraging a Vision Transformer Model to Improve Diagnostic Accuracy of Cardiac Amyloidosis With Cardiac Magnetic Resonance. JACC. Cardiovascular imaging. 18(3). 278–290. 2 indexed citations
9.
Chen, David, Nakeya Dewaswala, Shivaram P. Arunachalam, et al.. (2022). Deep Neural Network for Cardiac Magnetic Resonance Image Segmentation. Journal of Imaging. 8(5). 149–149. 8 indexed citations
10.
Beck, Alain, Christine Nowak, David Chen, et al.. (2022). Risk-Based Control Strategies of Recombinant Monoclonal Antibody Charge Variants. Antibodies. 11(4). 73–73. 25 indexed citations
11.
Chen, David, Naveed Afzal, Sunghwan Sohn, et al.. (2018). Postoperative bleeding risk prediction for patients undergoing colorectal surgery. Surgery. 164(6). 1209–1216. 37 indexed citations
12.
André, Fabrice, Sara A. Hurvitz, Angelica Fasolo, et al.. (2016). Molecular Alterations and Everolimus Efficacy in Human Epidermal Growth Factor Receptor 2–Overexpressing Metastatic Breast Cancers: Combined Exploratory Biomarker Analysis From BOLERO-1 and BOLERO-3. Journal of Clinical Oncology. 34(18). 2115–2124. 135 indexed citations
13.
Hurvitz, Sara A., Ondrej Kalous, Dylan Conklin, et al.. (2015). In vitro activity of the mTOR inhibitor everolimus, in a large panel of breast cancer cell lines and analysis for predictors of response. Breast Cancer Research and Treatment. 149(3). 669–680. 46 indexed citations
14.
Chen, David. (2014). Designing Genetic Circuits for Memory and Communication. eScholarship (California Digital Library). 1 indexed citations
15.
Chen, David. (2012). Fast Online Lexicon Learning for Grounded Language Acquisition. Meeting of the Association for Computational Linguistics. 430–439. 18 indexed citations
16.
Chen, David & William B. Dolan. (2011). Collecting Highly Parallel Data for Paraphrase Evaluation. Meeting of the Association for Computational Linguistics. 190–200. 478 indexed citations breakdown →
17.
Chen, David, Sam S. Tsai, Vijay Chandrasekhar, et al.. (2011). Residual Enhanced Visual Vectors for on-device image matching. 850–854. 28 indexed citations
18.
Chen, David, et al.. (2004). Tree Structure Maintenance in a Collaborative Genetic Software Engineering System. A M A Archives of Internal Medicine. 92(3). 308–13. 1 indexed citations
19.
Chen, David & Chengzheng Sun. (1999). Intention Preservation by Object Replication in Cooperative Graphics Editing Systems.. 216–227. 1 indexed citations
20.
Findler, Nicholas V. & David Chen. (1971). On the problems of time, retrieval of temporal relations, causality, and co-existence.. ACM SIGART Bulletin. 31. 6. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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