William J. Colburn
- Cancer Research top 0.5%
- Breast Cancer Treatment Studies 17
- Pathology and Forensic Medicine top 0.5%
- Breast Lesions and Carcinomas 13
- Dermatology top 2%
- Cancer and Skin Lesions 5
- Oncology top 5%
- Global Cancer Incidence and Screening 3
- Surgery top 5%
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- Neuroendocrine regulation and behavior 6
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- Stress Responses and Cortisol 4
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- AI in cancer detection 3
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- Evolutionary Psychology and Human Behavior 3
- Co-authors
- Melvin J. SilversteinJames WaismanParvis GamagamiBernard S. LewinskyEugene D. GiersonMichael D. LagiosDavid PollerGregory M. Senofsky
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
William J. Colburn
25 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 79
- Cancer Research 2.0k
- Pathology and Forensic Medicine 1.7k
- Dermatology 268
- Oncology 826
- Surgery 668
Countries citing papers authored by William J. Colburn
This map shows the geographic impact of William J. Colburn'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 William J. Colburn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William J. Colburn more than expected).
Fields of papers citing papers by William J. Colburn
This network shows the impact of papers produced by William J. Colburn. 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 William J. Colburn. The network helps show where William J. Colburn may publish in the future.
Co-authorship network
The 25 scholars most cited alongside William J. Colburn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 11 | |
| 2 | 2019 | 6 | |
| 3 | 2019 | 18 | |
| 4 | 2014 | 1 | |
| 5 | 2002 | 71 | |
| 6 | Quantitative nuclear morphometry by image analysis for prediction of recurrence of ductal carcinoma in situ of the breast. | 2001 | 28 |
| 7 | 1999 | 470 | |
| 8 | 1996 | 1 | |
| 9 | 1996 | 18 | |
| 10 | 1996 | 488 | |
| 11 | 1996 | 5 | |
| 12 | 1995 | 179 | |
| 13 | Predicting axillary node positivity in patients with invasive carcinoma of the breast by using a combination of T category and palpability. | 1995 | 77 |
| 14 | 1994 | 319 | |
| 15 | 1994 | 185 | |
| 16 | 1994 | 2 | |
| 17 | 1992 | 110 | |
| 18 | Axillary lymphadenectomy for intraductal carcinoma of the breast. | 1991 | 67 |
| 19 | 1991 | 14 | |
| 20 | 1989 | 65 |
About William J. Colburn
William J. Colburn is a scholar working on Cancer Research, Behavioral Neuroscience and Pathology and Forensic Medicine, having authored 25 papers that have together received 2.4k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (17 papers), Breast Lesions and Carcinomas (13 papers), Neuroendocrine regulation and behavior (6 papers), Cancer and Skin Lesions (5 papers), Stress Responses and Cortisol (4 papers), Global Cancer Incidence and Screening (3 papers), AI in cancer detection (3 papers) and Evolutionary Psychology and Human Behavior (3 papers). The work is most often cited by research in Cancer Research (2.0k citations), Pathology and Forensic Medicine (1.7k citations) and Dermatology (268 citations). William J. Colburn has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Melvin J. Silverstein, James Waisman, Parvis Gamagami, Bernard S. Lewinsky, Eugene D. Gierson, Michael D. Lagios, David Poller, Gregory M. Senofsky, Pamela H. Craig and Susan Groshen. Their work appears in journals such as Cancer, Stress, European Journal of Cancer, The FASEB Journal and Autonomic Neuroscience.
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.