William D’Angelo

3.3k citations
33 papers · 2.4k · 1 hit paper · h-index 16

Impact in

Papers in

William D’Angelo

30 papers receiving 2.1k citations

William D’Angelo's Hit Papers

Pathologic observations in systemic sclerosis (scleroderma) 1969 · 936 citations
9360+19+38Years since publication250500750

Peers

William D’Angelo
Comparison fields: 5 of 97
  • Pathology and Forensic Medicine 1.5k
  • Dermatology 426
  • Rheumatology 484
  • Immunology 501
  • Epidemiology 378
Replace Voon H Ong with:
Voon H Ong United Kingdom
John Varga United States
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Steven O’Reilly United Kingdom
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Percival D. Sampaio‐Barros Brazil
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Citations per field
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Citations per year

Countries citing papers authored by William D’Angelo

Since Specialization
Citations

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

Fields of papers citing papers by William D’Angelo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William D’Angelo. 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 D’Angelo. The network helps show where William D’Angelo may publish in the future.

Co-authors

The 25 scholars most cited alongside William D’Angelo, 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 William D’Angelo Line = papers co-authored together William D’Angelo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Pathologic observations in systemic sclerosis (scleroderma)
Hit paper breakdown →
1969936
2 1975324
3 1980320
4
The modified Rodnan skin score is an accurate reflection of skin biopsy thickness in systemic sclerosis.
1998231
5 1979152
6 1988108
7 202030
8 197930
9 197729
10 197325
11 200823
12 201622
13 202021
14 197521
15 201720
16 201817
17 20249
18 20219
19 19799
20 20228

About William D’Angelo

William D’Angelo is a scholar working on Pathology and Forensic Medicine, Surgery, Molecular Biology, Epidemiology and Rheumatology, having authored 33 papers that have together received 2.4k indexed citations. Recurring topics across this work include Systemic Sclerosis and Related Diseases (9 papers), Tissue Engineering and Regenerative Medicine (4 papers), Inflammatory Myopathies and Dermatomyositis (3 papers), Extracellular vesicles in disease (3 papers), Electrospun Nanofibers in Biomedical Applications (3 papers), Mast cells and histamine (3 papers), Systemic Lupus Erythematosus Research (2 papers) and Connective Tissue Growth Factor Research (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (1.5k citations), Dermatology (426 citations), Rheumatology (484 citations), Immunology (501 citations) and Epidemiology (378 citations). William D’Angelo has collaborated with scholars based in United States, China and France. Frequent co-authors include Alfonse T. Masi, James F. Fries, Lawrence Shulman, Thomas A. Medsger, Sidney R. Block, J B Winfield, C L Christian, Michael D. Lockshin, Gerald P. Rodnan and Gordon C. Sharp. Their work appears in journals such as The American Journal of Medicine, Science Advances, IEEE Transactions on Affective Computing, Stem Cell Research & Therapy and The Journal of Immunology.

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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