Linda Coyle

2.3k total citations · 1 hit paper
33 papers, 1.7k citations indexed

About

Linda Coyle is a scholar working on Artificial Intelligence, Molecular Biology and Oncology. According to data from OpenAlex, Linda Coyle has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 6 papers in Molecular Biology and 5 papers in Oncology. Recurrent topics in Linda Coyle's work include Topic Modeling (10 papers), Machine Learning in Healthcare (8 papers) and Biomedical Text Mining and Ontologies (5 papers). Linda Coyle is often cited by papers focused on Topic Modeling (10 papers), Machine Learning in Healthcare (8 papers) and Biomedical Text Mining and Ontologies (5 papers). Linda Coyle collaborates with scholars based in United States, United Kingdom and Canada. Linda Coyle's co-authors include Gladys Block, Anne M. Hartman, Jennifer L. Stevens, Xiao‐Cheng Wu, André Gonçalves, Ana Paula Sales, Priyadip Ray, Braden Soper, Albert R. Hollenbeck and Amy F. Subar and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and JNCI Journal of the National Cancer Institute.

In The Last Decade

Linda Coyle

32 papers receiving 1.6k 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.

Design and Serendipity in Establishing a Large Cohort with Wide Dietary Intake Distributions

2001 505 citations Arthur Schatzkin, Amy F. Subar et al. American Journal of Epidemiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Linda Coyle United States	14	504	406	304	216	215	33	1.7k
R. L. Prentice United States	16	355 0.7×	135 0.3×	232 0.8×	157 0.7×	107 0.5×	33	1.7k
Dipankar Bandyopadhyay United States	28	125 0.2×	244 0.6×	237 0.8×	235 1.1×	344 1.6×	182	2.6k
Young Ae Kim South Korea	28	316 0.6×	138 0.3×	701 2.3×	201 0.9×	494 2.3×	132	2.6k
Yu Rang Park South Korea	20	165 0.3×	217 0.5×	179 0.6×	97 0.4×	287 1.3×	121	1.6k
Thomas Louis United States	18	239 0.5×	81 0.2×	440 1.4×	117 0.5×	263 1.2×	28	2.1k
Monica Daeges United States	18	193 0.4×	117 0.3×	542 1.8×	120 0.6×	115 0.5×	24	1.9k
Reed T. Sutton Canada	11	272 0.5×	329 0.8×	104 0.3×	76 0.4×	146 0.7×	21	1.9k
Binbing Yu United States	29	271 0.5×	143 0.4×	903 3.0×	416 1.9×	278 1.3×	92	3.0k
Lilly Q. Yue United States	17	181 0.4×	91 0.2×	183 0.6×	303 1.4×	262 1.2×	43	2.3k
Md. Mohaimenul Islam Taiwan	31	190 0.4×	321 0.8×	194 0.6×	259 1.2×	328 1.5×	92	3.0k

Countries citing papers authored by Linda Coyle

Since Specialization

Citations

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

Fields of papers citing papers by Linda Coyle

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linda Coyle

This figure shows the co-authorship network connecting the top 25 collaborators of Linda Coyle. A scholar is included among the top collaborators of Linda Coyle 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 Linda Coyle. Linda Coyle 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

Hanson, Heidi A., et al.. (2024). Machine learning and deep learning tools for the automated capture of cancer surveillance data. JNCI Monographs. 2024(65). 145–151. 6 indexed citations

Chen, Huann‐Sheng, Serban Negoita, Steven M. Schwartz, et al.. (2024). Toward real-time reporting of cancer incidence: methodology, pilot study, and SEER Program implementation. JNCI Monographs. 2024(65). 123–131. 1 indexed citations

Danciu, Ioana, Hong‐Jun Yoon, Jamaludin Mohd‐Yusof, et al.. (2023). Deep learning uncertainty quantification for clinical text classification. Journal of Biomedical Informatics. 149. 104576–104576. 3 indexed citations

Blanchard, Andrew E., Shang Gao, Hong‐Jun Yoon, et al.. (2022). A Keyword-Enhanced Approach to Handle Class Imbalance in Clinical Text Classification. IEEE Journal of Biomedical and Health Informatics. 26(6). 2796–2803. 10 indexed citations

Coyle, Linda, et al.. (2021). Virtual fracture liaison clinics in the COVID era: an initiative to maintain fracture prevention services during the pandemic associated with positive patient experience. Osteoporosis International. 32(6). 1221–1226. 12 indexed citations

Gao, Shang, Ioana Danciu, Eric B. Durbin, et al.. (2021). Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types. Journal of Biomedical Informatics. 125. 103957–103957. 37 indexed citations

Gao, Shang, Mohammed Alawad, Hong‐Jun Yoon, et al.. (2021). Deep active learning for classifying cancer pathology reports. BMC Bioinformatics. 22(1). 113–113. 25 indexed citations

Gao, Shang, Mohammed Alawad, M. Todd Young, et al.. (2021). Limitations of Transformers on Clinical Text Classification. IEEE Journal of Biomedical and Health Informatics. 25(9). 3596–3607. 104 indexed citations

Klasky, Hilda, John Gounley, Mohammed Alawad, et al.. (2020). Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports. Journal of Biomedical Informatics. 110. 103564–103564. 10 indexed citations

10.

Alawad, Mohammed, Hong‐Jun Yoon, Shang Gao, et al.. (2020). Privacy-Preserving Deep Learning NLP Models for Cancer Registries. IEEE Transactions on Emerging Topics in Computing. 9(3). 1219–1230. 31 indexed citations

11.

Gao, Shang, Mohammed Alawad, Lynne Penberthy, et al.. (2020). Using case-level context to classify cancer pathology reports. PLoS ONE. 15(5). e0232840–e0232840. 15 indexed citations

12.

Morawski, Bożena M, et al.. (2020). Impact of Linkage to the Social Security Administration on Follow-up Completeness and Cancer Relative Survival Estimates in 2 New SEER Registries: 2000-2016 Diagnosis Years.. PubMed. 47(2). 37–47. 2 indexed citations

13.

Gonçalves, André, Priyadip Ray, Braden Soper, et al.. (2020). Generation and evaluation of synthetic patient data. BMC Medical Research Methodology. 20(1). 108–108. 223 indexed citations

14.

Gao, Shang, John X. Qiu, Mohammed Alawad, et al.. (2019). Classifying cancer pathology reports with hierarchical self-attention networks. Artificial Intelligence in Medicine. 101. 101726–101726. 40 indexed citations

15.

Alawad, Mohammed, Shang Gao, John X. Qiu, et al.. (2019). Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks. Journal of the American Medical Informatics Association. 27(1). 89–98. 56 indexed citations

16.

Coyle, Linda, Kathleen A. Cronin, Clara Lam, et al.. (2016). Validation of prostate‐specific antigen laboratory values recorded in Surveillance, Epidemiology, and End Results registries. Cancer. 123(4). 697–703. 26 indexed citations

17.

Pickering, Cynthia, et al.. (2016). Community College STEM Pathways Guide: A Collaborative Online System for Design and Implementation of STEM Pathway Programs. 158–164. 4 indexed citations

18.

Schatzkin, Arthur, Amy F. Subar, Frances E. Thompson, et al.. (2001). Design and Serendipity in Establishing a Large Cohort with Wide Dietary Intake Distributions. American Journal of Epidemiology. 154(12). 1119–1125. 505 indexed citations breakdown →

19.

Block, Gladys, et al.. (1994). Revision of Dietary Analysis Software for the Health Habits and History Questionnaire. American Journal of Epidemiology. 139(12). 1190–1196. 261 indexed citations

20.

Block, Gladys, et al.. (1989). A DIETARY AND RISK FACTOR QUESTIONNAIRE AND ANALYSIS SYSTEM FOR PERSONAL COMPUTERS. American Journal of Epidemiology. 129(2). 445–449. 78 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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