Andrew T. Girvin

3.4k total citations · 1 hit paper
15 papers, 437 citations indexed

About

Andrew T. Girvin is a scholar working on Artificial Intelligence, Neurology and Oncology. According to data from OpenAlex, Andrew T. Girvin has authored 15 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Neurology and 4 papers in Oncology. Recurrent topics in Andrew T. Girvin's work include Machine Learning in Healthcare (4 papers), Long-Term Effects of COVID-19 (4 papers) and Cancer Immunotherapy and Biomarkers (3 papers). Andrew T. Girvin is often cited by papers focused on Machine Learning in Healthcare (4 papers), Long-Term Effects of COVID-19 (4 papers) and Cancer Immunotherapy and Biomarkers (3 papers). Andrew T. Girvin collaborates with scholars based in United States, Croatia and United Kingdom. Andrew T. Girvin's co-authors include Morgan Huse, Lawrence O. Klein, Michael S. Kuhns, Mark M. Davis, Thomas L. Ciardelli, Balaji M. Rao, Douglas A. Lauffenburger, K. Dane Wittrup, Christopher G. Chute and Melissa Haendel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Immunity.

In The Last Decade

Andrew T. Girvin

13 papers receiving 430 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Coding long COVID: characterizing a new disease through an ICD-10 lens

2023 84 citations Emily Pfaff, Charisse Madlock‐Brown et al. BMC Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew T. Girvin United States	8	240	97	95	90	69	15	437
Nouar Qutob Palestinian Territory	9	113 0.5×	184 1.9×	111 1.2×	36 0.4×	34 0.5×	16	363
Indre Piragyte South Korea	7	90 0.4×	130 1.3×	25 0.3×	29 0.3×	4 0.1×	11	284
Satoshi Tsuji Japan	12	133 0.6×	186 1.9×	107 1.1×	16 0.2×	8 0.1×	40	482
Kyle Kuszpit United States	13	23 0.1×	144 1.5×	80 0.8×	41 0.5×	168 2.4×	20	540
Molly Sullivan United States	11	141 0.6×	139 1.4×	28 0.3×	5 0.1×	66 1.0×	18	578
Gefei Alex Zhu United States	13	40 0.2×	209 2.2×	113 1.2×	11 0.1×	15 0.2×	21	487
Ann Marie Weideman United States	8	44 0.2×	61 0.6×	57 0.6×	68 0.8×	7 0.1×	24	359
Timothy Chan United States	4	82 0.3×	144 1.5×	53 0.6×	26 0.3×	8 0.1×	5	309
WooRam Jung South Korea	11	58 0.2×	306 3.2×	27 0.3×	21 0.2×	31 0.4×	15	607
Yunhai Dai China	10	24 0.1×	125 1.3×	20 0.2×	30 0.3×	99 1.4×	27	385

Countries citing papers authored by Andrew T. Girvin

Since Specialization

Citations

This map shows the geographic impact of Andrew T. Girvin'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 Andrew T. Girvin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew T. Girvin more than expected).

Fields of papers citing papers by Andrew T. Girvin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew T. Girvin. 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 Andrew T. Girvin. The network helps show where Andrew T. Girvin may publish in the future.

Co-authorship network of co-authors of Andrew T. Girvin

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew T. Girvin. A scholar is included among the top collaborators of Andrew T. Girvin 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 Andrew T. Girvin. Andrew T. Girvin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Kahn, Michael G., Tellen D. Bennett, Rachel Deer, et al.. (2025). Identifying who has long COVID in the USA: a machine learning approach using N3C data. UNC Libraries.

Gersing, Kenneth, Sam Michael, Fred Prior, et al.. (2024). Implementing Data Governance with Multi-Modal Privacy-Preserving Record Linkages between Restricted and Public Open Enclaves. International Journal for Population Data Science. 9(5).

Sidky, Hythem, Kristen Hansen, Andrew T. Girvin, et al.. (2024). Assessing the effect of selective serotonin reuptake inhibitors in the prevention of post-acute sequelae of COVID-19. Computational and Structural Biotechnology Journal. 24. 115–125. 9 indexed citations

Pfaff, Emily, Andrew T. Girvin, Hiral Master, et al.. (2023). De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository. Journal of the American Medical Informatics Association. 30(7). 1305–1312. 9 indexed citations

Pfaff, Emily, Charisse Madlock‐Brown, John M. Baratta, et al.. (2023). Coding long COVID: characterizing a new disease through an ICD-10 lens. BMC Medicine. 21(1). 58–58. 84 indexed citations breakdown →

Kerchberger, V. Eric, Melissa Haendel, Wei‐Qi Wei, et al.. (2023). De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository. UNC Libraries. 1 indexed citations

Sidky, Hythem, Jessica C. Young, Andrew T. Girvin, et al.. (2023). Data quality considerations for evaluating COVID-19 treatments using real world data: learnings from the National COVID Cohort Collaborative (N3C). BMC Medical Research Methodology. 23(1). 46–46. 7 indexed citations

Leese, Peter, Adit Anand, Andrew T. Girvin, et al.. (2023). Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs. Journal of the American Medical Informatics Association. 30(6). 1125–1136. 5 indexed citations

Weinstock, Chana, Laura L. Fernandes, Elaine Chang, et al.. (2020). Impact of timing of antibiotic use on clinical outcomes in patients with urothelial cancer treated with immune checkpoint inhibitors (ICIs).. Journal of Clinical Oncology. 38(15_suppl). 5045–5045. 2 indexed citations

10.

Anscher, Mitchell S., Shaily Arora, Chana Weinstock, et al.. (2020). Impact of radiotherapy on risk of adverse events in patients receiving immunotherapy: A U.S. Food and Drug Administration pooled analysis.. Journal of Clinical Oncology. 38(15_suppl). 3018–3018. 3 indexed citations

11.

Vellanki, Paz J., Shanthi Marur, Pallavi S. Mishra‐Kalyani, et al.. (2020). Evaluation of the correlation between antibiotic use and survival in patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) treated with immune checkpoint inhibitors (ICIs).. Journal of Clinical Oncology. 38(15_suppl). 6509–6509. 6 indexed citations

12.

Kuhns, Michael S., Andrew T. Girvin, Lawrence O. Klein, et al.. (2010). Evidence for a functional sidedness to the αβTCR. Proceedings of the National Academy of Sciences. 107(11). 5094–5099. 65 indexed citations

13.

Huse, Morgan, et al.. (2007). Spatial and Temporal Dynamics of T Cell Receptor Signaling with a Photoactivatable Agonist. Immunity. 27(1). 76–88. 191 indexed citations

14.

Rao, Balaji M., Andrew T. Girvin, Thomas L. Ciardelli, Douglas A. Lauffenburger, & K. Dane Wittrup. (2003). Interleukin-2 mutants with enhanced -receptor subunit binding affinity. Protein Engineering Design and Selection. 16(12). 1081–1087. 47 indexed citations

15.

Daley, Andrew J., Andrew T. Girvin, Stuart Kauffman, Peter R. Wills, & Daniel Yamins. (2002). Simulation of a Chemical Autonomous Agent. Zeitschrift für Physikalische Chemie. 216(1). 8 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.

Explore authors with similar magnitude of impact