Ivy Lee

465 total citations
14 papers, 272 citations indexed

About

Ivy Lee is a scholar working on Public Health, Environmental and Occupational Health, Oncology and Health. According to data from OpenAlex, Ivy Lee has authored 14 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Public Health, Environmental and Occupational Health, 3 papers in Oncology and 2 papers in Health. Recurrent topics in Ivy Lee's work include Digital Imaging in Medicine (3 papers), Cutaneous Melanoma Detection and Management (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Ivy Lee is often cited by papers focused on Digital Imaging in Medicine (3 papers), Cutaneous Melanoma Detection and Management (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). Ivy Lee collaborates with scholars based in United States and Denmark. Ivy Lee's co-authors include Howard I. Maïbach, Carrie Kovarik, Trilokraj Tejasvi, Jules B. Lipoff, Karen Edison, Michael Abrouk, Adam Yen, Jack Resneck, Matthew B. Fitzgerald and Justin Ko and has published in prestigious journals such as Journal of the American Academy of Dermatology, American Journal of Clinical Dermatology and Archives of Dermatological Research.

In The Last Decade

Ivy Lee

9 papers receiving 263 citations

Peers

Ivy Lee
Paula W. Feng United States
Sandhya Yadav United States
Sepideh Ashrafzadeh United States
Aarti Pandya United States
Marije van Melle Netherlands
Ivy Lee
Citations per year, relative to Ivy Lee Ivy Lee (= 1×) peers Judy Paisley

Countries citing papers authored by Ivy Lee

Since Specialization
Citations

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

Fields of papers citing papers by Ivy Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivy Lee

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

All Works

14 of 14 papers shown
2.
Lee, Ivy. (2025). Artificial Intelligence in Teledermatology. Dermatologic Clinics. 43(4). 553–561.
3.
Schlessinger, Daniel I., Justin Ko, Ivy Lee, Veronica Rotemberg, & Roberto A. Novoa. (2025). Augmented Intelligence and Dermatology – Part I: Core Concepts and Applications. Journal of the American Academy of Dermatology. 94(1). 1–8. 1 indexed citations
4.
Wongvibulsin, Shannon, et al.. (2025). Augmented Intelligence and Dermatology - Part II: Bias, Benchmarks, Guidelines, Ethics, Regulation, and Future Directions. Journal of the American Academy of Dermatology. 94(1). 11–19. 1 indexed citations
5.
Wongvibulsin, Shannon & Ivy Lee. (2025). Artificial Intelligence and Dermatology. JAMA Dermatology. 161(3). 344–344. 1 indexed citations
6.
Lee, Ivy, Jenna Lester, Veronica Rotemberg, et al.. (2024). Engaging industry effectively and ethically in artificial intelligence from the Augmented Artificial Intelligence Committee Standards Workgroup. Journal of the American Academy of Dermatology. 91(2). 312–314. 1 indexed citations
7.
Gui, Haiwen, Daniel I. Schlessinger, Jenna Lester, et al.. (2024). 50830 Dermatologists’ perspectives on the usage of AI-based large language models in practice- an exploratory survey. Journal of the American Academy of Dermatology. 91(3). AB30–AB30. 1 indexed citations
8.
Lee, Ivy, et al.. (2021). Evaluation of Teledermatology Practice Guidelines and Recommendations for Improvement. Telemedicine Journal and e-Health. 28(1). 115–120. 9 indexed citations
9.
Lee, Ivy, et al.. (2020). Telehealth: Helping your patients and practice survive and thrive during the COVID-19 crisis with rapid quality implementation. Journal of the American Academy of Dermatology. 82(5). 1213–1214. 98 indexed citations
10.
Lee, Kachiu C., Ivy Lee, Jean‐Phillip Okhovat, et al.. (2020). Innovation interest within dermatology: a needs assessment for novel thought processes. Archives of Dermatological Research. 313(10). 885–888. 3 indexed citations
11.
Kovarik, Carrie, Ivy Lee, Justin Ko, et al.. (2019). Commentary: Position statement on augmented intelligence (AuI). Journal of the American Academy of Dermatology. 81(4). 998–1000. 25 indexed citations
12.
Resneck, Jack, Michael Abrouk, Adam Yen, et al.. (2016). Choice, Transparency, Coordination, and Quality Among Direct-to-Consumer Telemedicine Websites and Apps Treating Skin Disease. JAMA Dermatology. 152(7). 768–768. 69 indexed citations
13.
Lee, Ivy & Howard I. Maïbach. (2006). Pharmionics in Dermatology. American Journal of Clinical Dermatology. 7(4). 231–236. 62 indexed citations
14.
Lee, Ivy. (2001). Probing the issues of reconciliation more than fifty years after the Asia-Pacific War. East Asia. 19(4). 39–54. 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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