Stephanie D. Gan

1.2k citations
12 papers · 817 indexed · 1 hit paper · h-index 10
Topics
Dermatologic Treatments and Research (4 papers)Cancer and Skin Lesions (3 papers)Meta-analysis and systematic reviews (2 papers)
Partner nations
United StatesGermany

In The Last Decade

Stephanie D. Gan

12 papers receiving 785 citations

Hit Papers

Enzyme Immunoassay and Enzyme-Linked Immunosorbent Assay20132026201720212013100200300400

Peers

Stephanie D. Gan
Comparison fields: 5 of 126
  • Dermatology 309
  • Molecular Biology 240
  • Epidemiology 160
  • Biomedical Engineering 157
  • Immunology 95
Replace Keiko Sakamoto with:
Keiko Sakamoto Japan
Norbert Wikonkál Hungary
A.D. Pearse United Kingdom
M. Venkataraman United States
Alfredo Aguirre United States
Vidhi Shah United States
Călin Giurcăneanu Romania
Firas Al‐Niaimi United Kingdom
Abdulmajeed Alajlan Saudi Arabia
Christopher G. Bunick United States
Stephanie D. Gan relative to Keiko Sakamoto Japan Keiko Sakamoto's profile →
Citations per field
00.5×1.5×1.9×
Keiko Sakamoto · 1×
Citations per year

Countries citing papers authored by Stephanie D. Gan

Since Specialization
Citations

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

Fields of papers citing papers by Stephanie D. Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephanie D. Gan. 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 Stephanie D. Gan. The network helps show where Stephanie D. Gan may publish in the future.

Co-authorship network of co-authors of Stephanie D. Gan

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 9
2 12
3 19
4 32
5
Treatment of Pearly Penile Papules with Fractionated CO2 Laser.
3
6
Papular scars: an addition to the acne scar classification scheme.
8
7 18
8 16
9
Enzyme Immunoassay and Enzyme-Linked Immunosorbent Assaybreakdown →
415
10 133
11 30
12 122

About Stephanie D. Gan

Stephanie D. Gan is a scholar working on Dermatology, Statistics, Probability and Uncertainty and Biochemistry, having authored 12 papers that have together received 817 indexed citations. Recurring topics across this work include Dermatologic Treatments and Research (4 papers), Cancer and Skin Lesions (3 papers) and Meta-analysis and systematic reviews (2 papers). The work is most often cited by research in Dermatology (309 citations), Urology (50 citations) and Epidemiology (160 citations). Stephanie D. Gan has collaborated with scholars based in United States and Germany. Frequent co-authors include K R Patel, Emmy Graber, Judy Jones, Donald R. Miller, Marie‐France Demierre, Christine A. Liang, Nellie Konnikov, Thomas M. Rünger, Michael Bigby and Jag Bhawan. Their work appears in journals such as Cancer, Journal of Investigative Dermatology and Journal of the American Academy of Dermatology.

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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