Daniel M. Siegel

2.6k total citations
103 papers, 1.7k citations indexed

About

Daniel M. Siegel is a scholar working on Dermatology, Epidemiology and Oncology. According to data from OpenAlex, Daniel M. Siegel has authored 103 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Dermatology, 37 papers in Epidemiology and 28 papers in Oncology. Recurrent topics in Daniel M. Siegel's work include Nonmelanoma Skin Cancer Studies (30 papers), Cutaneous Melanoma Detection and Management (25 papers) and Cutaneous lymphoproliferative disorders research (12 papers). Daniel M. Siegel is often cited by papers focused on Nonmelanoma Skin Cancer Studies (30 papers), Cutaneous Melanoma Detection and Management (25 papers) and Cutaneous lymphoproliferative disorders research (12 papers). Daniel M. Siegel collaborates with scholars based in United States, Denmark and Netherlands. Daniel M. Siegel's co-authors include Jared Jagdeo, Neil Brody, Robert L. McDonald, Andrew Mamalis, Orit Markowitz, Alan R. Shalita, Edward J M Monk, James Spencer, Gordon McKenzie and Hadar Lev‐Tov and has published in prestigious journals such as JAMA, SHILAP Revista de lepidopterología and The Journal of Finance.

In The Last Decade

Daniel M. Siegel

96 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel M. Siegel United States 22 645 451 429 304 237 103 1.7k
Bernhard Lange‐Asschenfeldt Germany 27 574 0.9× 446 1.0× 966 2.3× 288 0.9× 837 3.5× 56 2.5k
Anthony Rossi United States 25 1.1k 1.7× 993 2.2× 965 2.2× 93 0.3× 281 1.2× 155 2.3k
Pietro Puddu Italy 30 937 1.5× 430 1.0× 510 1.2× 71 0.2× 409 1.7× 88 3.0k
Richard F. Wagner United States 24 1.0k 1.6× 855 1.9× 776 1.8× 78 0.3× 385 1.6× 179 2.4k
Petr Arenberger Czechia 22 681 1.1× 239 0.5× 259 0.6× 51 0.2× 316 1.3× 117 2.0k
Suephy C. Chen United States 35 1.8k 2.8× 1.1k 2.3× 1.2k 2.9× 122 0.4× 298 1.3× 199 3.7k
Eckhard W. Breitbart Germany 21 1.0k 1.6× 626 1.4× 1.2k 2.9× 89 0.3× 461 1.9× 67 2.2k
Menno A. de Rie Netherlands 33 2.1k 3.2× 988 2.2× 566 1.3× 244 0.8× 445 1.9× 133 4.8k
Robert Strohal Austria 30 725 1.1× 271 0.6× 331 0.8× 260 0.9× 320 1.4× 90 2.8k
Fang Wang China 25 471 0.7× 159 0.4× 141 0.3× 129 0.4× 562 2.4× 160 2.4k

Countries citing papers authored by Daniel M. Siegel

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Siegel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Siegel. 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 Daniel M. Siegel. The network helps show where Daniel M. Siegel may publish in the future.

Co-authorship network of co-authors of Daniel M. Siegel

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

All Works

20 of 20 papers shown
1.
Brownstone, Nicholas, Brian Berman, Roger I. Ceilley, et al.. (2023). Incorporating Prognostic Gene Expression Profile Assays into the Management of Cutaneous Melanoma: An Expert Consensus Panel. SKIN The Journal of Cutaneous Medicine. 7(1). 556–569. 5 indexed citations
2.
3.
Gordon, Dan & Daniel M. Siegel. (2020). Machine learning and the future of Medicare fraud detection. Journal of the American Academy of Dermatology. 83(2). e133–e133. 4 indexed citations
4.
5.
Ferris, Laura K., et al.. (2018). Real-world performance and utility of a noninvasive gene expression assay to evaluate melanoma risk in pigmented lesions. Melanoma Research. 28(5). 478–482. 46 indexed citations
6.
Siegel, Daniel M., et al.. (2018). Dangerous plants in dermatology: Legal and controlled. Clinics in Dermatology. 36(3). 399–419. 4 indexed citations
7.
Kazlouskaya, Viktoryia, et al.. (2017). Folliculocystic and collagen hamartoma of tuberous sclerosis: A new case in a female patient and review of literature. Journal of Cutaneous Pathology. 45(1). 67–70. 8 indexed citations
8.
Ulrich, Martina, Amanda Bienenfeld, Gordon McKenzie, et al.. (2016). Differentiation of Basal Cell Carcinoma Subtypes in Multi-Beam Swept Source Optical Coherence Tomography (MSS-OCT).. PubMed. 15(5). 545–50. 12 indexed citations
9.
Siegel, Daniel M.. (2016). Coding changes for 2016.. PubMed. 97(4). 285;286;301–285;286;301. 1 indexed citations
10.
Siegel, Daniel M.. (2016). Electronic health records, autocoding, and ewe: don't be a sheep!. PubMed. 97(6). 386–8. 1 indexed citations
11.
Markowitz, Orit, et al.. (2016). Defining Field Cancerization of the Skin Using Noninvasive Optical Coherence Tomography Imaging to Detect and Monitor Actinic Keratosis in Ingenol Mebutate 0.015%- Treated Patients.. PubMed. 9(5). 18–25. 17 indexed citations
12.
Bienenfeld, Amanda, et al.. (2016). Improved patient satisfaction using ingenol mebutate gel 0.015% for the treatment of facial actinic keratoses: a prospective pilot study. Clinical Cosmetic and Investigational Dermatology. 9. 89–89. 3 indexed citations
13.
Fluhr, Joachim W., et al.. (2013). Optical Coherence Tomography–Based Optimization of Mohs Micrographic Surgery of Basal Cell Carcinoma: A Pilot Study. Dermatologic Surgery. 39(4). 627–633. 57 indexed citations
14.
Siegel, Daniel M., et al.. (2013). Achieving hemostasis in dermatology – Part 1: Preoperative, intraoperative, and postoperative management. Indian Dermatology Online Journal. 4(2). 71–81. 11 indexed citations
15.
Monk, Edward J M, Alan R. Shalita, & Daniel M. Siegel. (2010). Clinical applications of non-antimicrobial tetracyclines in dermatology. Pharmacological Research. 63(2). 130–145. 85 indexed citations
16.
Siegel, Daniel M.. (2002). Resolution in digital imaging: Enough already?. Seminars in Cutaneous Medicine and Surgery. 21(3). 209–215. 13 indexed citations
17.
Kalish, Richard S., et al.. (1998). Experimental Rationale for Treatment of High-Risk Human Melanoma with Zinc Chloride Fixative Paste. Dermatologic Surgery. 24(9). 1021–1025. 9 indexed citations
18.
Siegel, Daniel M., et al.. (1996). Surgical pearl: A novel cost-effective approach to wound closure and dressings. Journal of the American Academy of Dermatology. 34(4). 673–675. 6 indexed citations
19.
Siegel, Daniel M.. (1989). A New Scalpel Handle for the Cutaneous Surgeon. The Journal of Dermatologic Surgery and Oncology. 15(12). 1251–1251. 9 indexed citations
20.
Giri, Shri N., Janet M. Benson, Daniel M. Siegel, Stuart A. Rice, & Mary J. Schiedt. (1975). Effects of Pretreatment with Anti-Inflammatory Drugs on Ozone-Induced Lung Damage in Rats. Experimental Biology and Medicine. 150(3). 810–813. 12 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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