Daniel G. Federman

147 papers receiving 4.2k citations

Daniel G. Federman's Hit Papers

Robot-Assisted Therapy for Long-Term Upper-Limb Impairment after Stroke 2010 · 1.0k citations
1.0k0+5+10Years since publication2505007501000

Peers

Daniel G. Federman
Comparison fields: 5 of 160
  • Rehabilitation 1.0k
  • Dermatology 510
  • Parasitology 235
  • Neurology 369
  • Epidemiology 687
Replace Peter J. Kelly with:
Peter J. Kelly Ireland
Efstratios Maltezos Greece
J. T. Scott United Kingdom
Carl J. Hauser United States
Dennis P. West United States
F. Aubin France
Robin Howard United Kingdom
Petra Büttner Germany
Martin Raftery United Kingdom
H. Zeidler Germany
Daniel G. Federman relative to Peter J. Kelly Ireland Peter J. Kelly's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel G. Federman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel G. Federman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel G. Federman, 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 Daniel G. Federman Line = papers co-authored together Daniel G. Federman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Robot-Assisted Therapy for Long-Term Upper-Limb Impairment after Stroke
Hit paper breakdown →
20101004
2 2009322
3 2005182
4 2001130
5 2011116
6 2012106
7 200397
8 199994
9 200383
10 199583
11 200977
12 201171
13 200569
14
Common bacterial skin infections.
200169
15 200268
16 200967
17 200255
18 201154
19 200151
20 199950

About Daniel G. Federman

Daniel G. Federman is a scholar working on Dermatology, Oncology, Epidemiology, Surgery and Pharmacology, having authored 157 papers that have together received 4.4k indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (19 papers), Nonmelanoma Skin Cancer Studies (14 papers), Skin Protection and Aging (9 papers), Peripheral Artery Disease Management (9 papers), Psoriasis: Treatment and Pathogenesis (8 papers), Medicine and Dermatology Studies History (8 papers), Acupuncture Treatment Research Studies (7 papers) and Autoimmune Bullous Skin Diseases (6 papers). The work is most often cited by research in Rehabilitation (1.0k citations), Dermatology (510 citations), Parasitology (235 citations), Neurology (369 citations) and Epidemiology (687 citations). Daniel G. Federman has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Robert S. Kirsner, Jeffrey D. Kravetz, Fangchao Ma, Dawn M. Bravata, Peter Peduzzi, Robert Ringer, George F. Wittenberg, Lorie Richards, Christopher T. Bever and Todd H. Wagner. Their work appears in journals such as The American Journal of Medicine, Dermatologic Surgery, Journal of the American Academy of Dermatology, JAMA and Mayo Clinic Proceedings.

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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