Lynne Penberthy

4.2k total citations · 1 hit paper
62 papers, 2.8k citations indexed

About

Lynne Penberthy is a scholar working on Oncology, Genetics and Artificial Intelligence. According to data from OpenAlex, Lynne Penberthy has authored 62 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Oncology, 11 papers in Genetics and 11 papers in Artificial Intelligence. Recurrent topics in Lynne Penberthy's work include Global Cancer Incidence and Screening (10 papers), Hemoglobinopathies and Related Disorders (10 papers) and Topic Modeling (8 papers). Lynne Penberthy is often cited by papers focused on Global Cancer Incidence and Screening (10 papers), Hemoglobinopathies and Related Disorders (10 papers) and Topic Modeling (8 papers). Lynne Penberthy collaborates with scholars based in United States, Ukraine and United Kingdom. Lynne Penberthy's co-authors include Susan D. Roseff, Viktor E. Bovbjerg, Wally R. Smith, Imoigele P. Aisiku, James L. Levenson, Donna K. McClish, John D. Roberts, Bassam Dahman, Angela B. Mariotto and Ruth Etzioni and has published in prestigious journals such as Journal of Clinical Oncology, Annals of Internal Medicine and PLoS ONE.

In The Last Decade

Lynne Penberthy

62 papers receiving 2.8k 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.

Estimation of the Number of Women Living with Metastatic Breast Cancer in the United States

2017 381 citations Angela B. Mariotto, Ruth Etzioni et al. Cancer Epidemiology Biomarkers & Prevention profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lynne Penberthy United States	26	1.2k	761	559	534	396	62	2.8k
Ephraim P. Hochberg United States	42	1.2k 1.0×	1.2k 1.6×	396 0.7×	1.9k 3.5×	410 1.0×	148	5.2k
Gustaf Edgren Sweden	43	491 0.4×	885 1.2×	167 0.3×	980 1.8×	637 1.6×	149	5.0k
Giovanni Caocci Italy	24	873 0.7×	954 1.3×	420 0.8×	349 0.7×	136 0.3×	112	2.0k
Sandra Eloranta Sweden	31	638 0.5×	514 0.7×	135 0.2×	957 1.8×	290 0.7×	125	3.1k
Gerard Vreugdenhil Netherlands	40	458 0.4×	917 1.2×	391 0.7×	3.2k 5.9×	753 1.9×	165	5.0k
María A. López-Olivo United States	34	421 0.4×	673 0.9×	143 0.3×	974 1.8×	470 1.2×	134	4.4k
Joseph Pidala United States	39	767 0.6×	3.5k 4.6×	871 1.6×	1.1k 2.0×	433 1.1×	170	5.0k
Mei‐Jie Zhang United States	28	184 0.2×	674 0.9×	152 0.3×	454 0.9×	153 0.4×	112	2.5k
Carrie A. Thompson United States	28	631 0.5×	218 0.3×	188 0.3×	1.4k 2.7×	262 0.7×	183	2.9k
Jonathan Barratt United Kingdom	45	512 0.4×	1.7k 2.3×	103 0.2×	122 0.2×	751 1.9×	291	6.6k

Countries citing papers authored by Lynne Penberthy

Since Specialization

Citations

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

Fields of papers citing papers by Lynne Penberthy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lynne Penberthy

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

Tatalovich, Zaria, Li Zhu, Curt T. DellaValle, et al.. (2024). Landscape analysis of environmental data sources for linkage with SEER cancer patients database. JNCI Monographs. 2024(65). 132–144. 1 indexed citations

Hanson, Heidi A., et al.. (2024). Topological Interpretability for Deep Learning. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–11. 1 indexed citations

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

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

Golden, Todd, Huann‐Sheng Chen, Stephen M. Schwartz, et al.. (2023). Impact on the Volume of Pathology Reports Before and During the COVID-19 Pandemic in SEER Cancer Registries. Cancer Epidemiology Biomarkers & Prevention. 32(11). 1591–1598. 4 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

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

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

10.

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

11.

Bhattacharya, Tanmoy, Thomas Brettin, James H. Doroshow, et al.. (2019). AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing. Frontiers in Oncology. 9. 984–984. 22 indexed citations

12.

Mariotto, Angela B., Ruth Etzioni, Marc Hurlbert, Lynne Penberthy, & Musa Mayer. (2017). Estimation of the Number of Women Living with Metastatic Breast Cancer in the United States. Cancer Epidemiology Biomarkers & Prevention. 26(6). 809–815. 381 indexed citations breakdown →

13.

Miller, Dave P., Megan C. Roberts, Valentina I. Petkov, et al.. (2016). Breast cancer-specific survival in >4,600 patients with lymph node-positive (LN+) hormone receptor-positive (HR+) invasive breast cancer (BC) and 21-gene recurrence score® (RS) results in the SEER registries. Annals of Oncology. 27. vi45–vi45. 3 indexed citations

14.

Shak, Steven, Dave P. Miller, Nadia Howlader, et al.. (2016). Outcome disparities by age and 21-gene recurrence score® (RS) result in hormone receptor positive (HR+) breast cancer (BC). Annals of Oncology. 27. vi43–vi43. 8 indexed citations

15.

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

16.

Aisiku, Imoigele P., Wally R. Smith, Donna K. McClish, et al.. (2008). Comparisons of High Versus Low Emergency Department Utilizers in Sickle Cell Disease. Annals of Emergency Medicine. 53(5). 587–593. 99 indexed citations

17.

Cítero, Vanessa de Albuquerque, James L. Levenson, Donna K. McClish, et al.. (2007). The role of catastrophizing in sickle cell disease – The PiSCES project. Pain. 133(1). 39–46. 54 indexed citations

18.

McClish, Donna K., Lynne Penberthy, Viktor E. Bovbjerg, et al.. (2005). Health related quality of life in sickle cell patients: The PiSCES project. Health and Quality of Life Outcomes. 3(1). 50–50. 225 indexed citations

19.

Hillner, Bruce E., Marian McDonald, Christopher E. Desch, et al.. (1998). Costs of care associated with non-small-cell lung cancer in a commercially insured cohort.. Journal of Clinical Oncology. 16(4). 1420–1424. 46 indexed citations

20.

Penberthy, Lynne, et al.. (1993). Appendectomy incidental to cholecystectomy among elderly Medicare beneficiaries.. PubMed. 177(3). 288–94. 25 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