Lee Wheless

70 papers receiving 1.5k citations

Lee Wheless's Hit Papers

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging 2025 · 47 citations
470Years since publication10203040

Peers

Lee Wheless
Comparison fields: 5 of 113
  • Health Informatics 383
  • Rheumatology 176
  • Oncology 197
  • Epidemiology 229
  • Health Information Management 55
Replace Yuqun Zeng with:
Yuqun Zeng China
Henrik Olsson Sweden
Catarina Eloy Portugal
Sascha Gerdes Germany
Marlies Wakkee Netherlands
Vincenzo Venerito Italy
Aziz Nazha United States
Bengü Nisa Akay Türkiye
Min Kyu Kang South Korea
Philip J. Drew United Kingdom
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Countries citing papers authored by Lee Wheless

Since Specialization
Citations

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

Fields of papers citing papers by Lee Wheless

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lee Wheless, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lee Wheless Line = papers co-authored together Lee Wheless links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2023327
2 2020145
3 2010102
4 202381
5 201664
6 201451
7
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
Hit paper breakdown →
202547
8 202345
9 201939
10 201428
11 201027
12 201826
13 201025
14 201825
15 202325
16 202124
17 202124
18 202324
19 201223
20 201723

About Lee Wheless

Lee Wheless is a scholar working on Rheumatology, Epidemiology, Dermatology, Oncology and Health Information Management, having authored 76 papers that have together received 1.6k indexed citations. Recurring topics across this work include Nonmelanoma Skin Cancer Studies (19 papers), Cutaneous Melanoma Detection and Management (11 papers), Systemic Lupus Erythematosus Research (11 papers), Genetic Associations and Epidemiology (7 papers), Medical Coding and Health Information (6 papers), AI in cancer detection (6 papers), Artificial Intelligence in Healthcare and Education (4 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Health Informatics (383 citations), Rheumatology (176 citations), Oncology (197 citations), Epidemiology (229 citations) and Health Information Management (55 citations). Lee Wheless has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include April Barnado, Anthony J. Alberg, Leslie J. Crofford, James Randall Patrinely, Douglas Buckner Johnson, Robert J. Carroll, Joshua C. Denny, Carolyn Gall Casey, Rachel S. Goodman and Travis John Osterman. Their work appears in journals such as JAMA Dermatology, Journal of the American Academy of Dermatology, Lupus, Dermatologic Surgery and Arthritis Care & Research.

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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