Andrew Beers

2.7k total citations · 1 hit paper
24 papers, 970 citations indexed

About

Andrew Beers is a scholar working on Radiology, Nuclear Medicine and Imaging, Sociology and Political Science and Communication. According to data from OpenAlex, Andrew Beers has authored 24 papers receiving a total of 970 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Sociology and Political Science and 6 papers in Communication. Recurrent topics in Andrew Beers's work include Misinformation and Its Impacts (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Social Media and Politics (4 papers). Andrew Beers is often cited by papers focused on Misinformation and Its Impacts (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Social Media and Politics (4 papers). Andrew Beers collaborates with scholars based in United States, Switzerland and Belarus. Andrew Beers's co-authors include Jayashree Kalpathy–Cramer, Ken Chang, James M. Brown, Susan Ostmo, Deniz Erdoğmuş, Stratis Ioannidis, Michael F. Chiang, R.V. Paul Chan, Jennifer Dy and J. Peter Campbell and has published in prestigious journals such as SHILAP Revista de lepidopterología, Stroke and Clinical Cancer Research.

In The Last Decade

Andrew Beers

22 papers receiving 953 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.

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

2018 396 citations James M. Brown, J. Peter Campbell et al. JAMA Ophthalmology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrew Beers United States	13	555	266	206	138	113	24	970
Darvin Yi United States	12	778 1.4×	359 1.3×	212 1.0×	184 1.3×	134 1.2×	26	1.2k
Mikhail Milchenko United States	10	437 0.8×	467 1.8×	13 0.1×	53 0.4×	153 1.4×	23	1.1k
Andrew Miller Australia	15	806 1.5×	70 0.3×	752 3.7×	147 1.1×	33 0.3×	48	1.3k
Ximin Wang China	13	328 0.6×	361 1.4×	18 0.1×	85 0.6×	44 0.4×	29	1.1k
Georgios C. Manikis Greece	15	489 0.9×	136 0.5×	132 0.6×	73 0.5×	23 0.2×	65	795
Li Kuo Tan Malaysia	13	434 0.8×	51 0.2×	44 0.2×	53 0.4×	17 0.2×	63	874
Aikaterini Kotrotsou United States	16	712 1.3×	483 1.8×	13 0.1×	187 1.4×	156 1.4×	38	1.5k
Claudia Mello‐Thoms Australia	26	1.3k 2.3×	1000 3.8×	37 0.2×	704 5.1×	112 1.0×	137	2.5k
Sarthak Pati United States	11	443 0.8×	585 2.2×	12 0.1×	76 0.6×	166 1.5×	27	1.1k
Carson Lam United States	13	606 1.1×	275 1.0×	290 1.4×	106 0.8×	92 0.8×	25	1.1k

Countries citing papers authored by Andrew Beers

Since Specialization

Citations

This map shows the geographic impact of Andrew Beers'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 Beers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Beers more than expected).

Fields of papers citing papers by Andrew Beers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Beers

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Beers. A scholar is included among the top collaborators of Andrew Beers 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 Beers. Andrew Beers 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:

20 of 20 papers shown

Beers, Andrew, et al.. (2025). ElectionRumors2022: A Dataset of Election Rumors on Twitter During the 2022 U.S. Midterms. HOPE (Hauptbibliothek Open Publishing Environment) (University of Zurich). 5. 1 indexed citations

Beers, Andrew, et al.. (2025). WikiReddit: Tracing Information and Attention Flows Between Online Platforms. Proceedings of the International AAAI Conference on Web and Social Media. 19. 2434–2445.

Beers, Andrew, et al.. (2023). Selective and deceptive citation in the construction of dueling consensuses. Science Advances. 9(38). eadh1933–eadh1933. 3 indexed citations

Beers, Andrew, et al.. (2023). Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election. Proceedings of the International AAAI Conference on Web and Social Media. 17. 59–71. 4 indexed citations

Bak-Coleman, Joseph B., Ian Kennedy, Andrew Beers, et al.. (2022). Combining interventions to reduce the spread of viral misinformation. Nature Human Behaviour. 6(10). 1372–1380. 78 indexed citations

Beers, Andrew, Tom Wilson, & Kate Starbird. (2022). Demographics of an International Influence Operation Affecting Facebook Users in the United States. 1(4). 7 indexed citations

Kennedy, Ian, et al.. (2022). Repeat Spreaders and Election Delegitimization. SHILAP Revista de lepidopterología. 2. 18 indexed citations

Beers, Andrew, et al.. (2021). REJECTING SCIENCE WITH SCIENCE: BOUNDARY-WORK IN ANTI-MASK TWITTER REPLY THREADS DURING COVID-19. AoIR Selected Papers of Internet Research. 2 indexed citations

Chang, Ken, Andrew Beers, Jay Patel, et al.. (2020). Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density. Journal of the American College of Radiology. 17(12). 1653–1662. 37 indexed citations

10.

Hoebel, Katharina, Vincent Andrearczyk, Andrew Beers, et al.. (2020). An exploration of uncertainty information for segmentation quality assessment. ArODES (HES-SO (https://www.hes-so.ch/)). 55–55. 20 indexed citations

11.

Hoebel, Katharina, Jay Patel, Andrew Beers, et al.. (2020). Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of Glioblastoma. Radiology Artificial Intelligence. 3(1). e190199–e190199. 39 indexed citations

12.

Gerstner, Elizabeth R., Kyrre E. Emblem, Ken Chang, et al.. (2019). Bevacizumab Reduces Permeability and Concurrent Temozolomide Delivery in a Subset of Patients with Recurrent Glioblastoma. Clinical Cancer Research. 26(1). 206–212. 40 indexed citations

13.

Brown, James M., et al.. (2019). Abstract WMP17: Fully-Automated Ischemic Brain Infarct Volumetric Segmentation in Diffusion Weighted MR using Deep Learning. Stroke. 50(Suppl_1). 1 indexed citations

14.

Silva, Michael A., Jay Patel, Vasileios K. Kavouridis, et al.. (2019). Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture. World Neurosurgery. 131. e46–e51. 50 indexed citations

15.

Brown, James M., J. Peter Campbell, Andrew Beers, et al.. (2018). Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks. JAMA Ophthalmology. 136(7). 803–803. 396 indexed citations breakdown →

16.

Parsons, Michael, Katharina Hoebel, Andrew Beers, et al.. (2018). NCOG-04. EFFECTS OF PROTON RADIATION ON BRAIN STRUCTURE AND FUNCTION IN LOW GRADE GLIOMA. Neuro-Oncology. 20(suppl_6). vi173–vi173. 2 indexed citations

17.

Balagurunathan, Yoganand, Andrew Beers, Jayashree Kalpathy–Cramer, et al.. (2018). Semi‐automated pulmonary nodule interval segmentation using the NLST data. Medical Physics. 45(3). 1093–1107. 15 indexed citations

18.

Brown, James M., Jayashree Kalpathy–Cramer, Andrew Beers, et al.. (2018). Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning. Lincoln Repository (University of Lincoln). 22–22. 19 indexed citations

19.

Chang, Ken, Niranjan Balachandar, Carson Lam, et al.. (2018). Distributed deep learning networks among institutions for medical imaging. Journal of the American Medical Informatics Association. 25(8). 945–954. 199 indexed citations

20.

Curry, Sean, et al.. (2001). Integrated three-dimensional ciraniofacial mapping at the Craniofacial Research Instrumentation Laboratory/University of the Pacific. Seminars in Orthodontics. 7(4). 258–265. 19 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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