David E. Leaf

14.0k citations
111 papers · 4.9k indexed · 3 hit papers · h-index 36

David E. Leaf

103 papers receiving 4.8k citations

Hit Papers

Target Trial Emulation3782016202620192022250500750

Peers

David E. Leaf
Comparison fields: 5 of 148
  • Nephrology 1.3k
  • Internal Medicine 254
  • Infectious Diseases 985
  • Critical Care and Intensive Care Medicine 246
  • Oncology 1.2k
Replace Patompong Ungprasert with:
Patompong Ungprasert United States
Stuart D. Katz United States
Julio Núñez Spain
Jeremiah R. Brown United States
Leonardo Tamariz United States
Αlexandros Briasoulis United States
Sandra C. Bryant United States
Eric McArthur Canada
Manish M. Sood Canada
Feng Lin United States
David E. Leaf relative to Patompong Ungprasert United States Patompong Ungprasert's profile →
Citations per field
00.5×4.6×
Patompong Ungprasert · 1×
Citations per year

Countries citing papers authored by David E. Leaf

Since Specialization
Citations

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

Fields of papers citing papers by David E. Leaf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. Leaf. 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 David E. Leaf. The network helps show where David E. Leaf may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20239
2 20231
3 20237
4 20233
5 20233
6 202231
7 202220
8 20212
9 20200
10 202070
11 202071
12
COVID-19 and coagulation: bleeding and thrombotic manifestations of SARS-CoV-2 infectionbreakdown →
2020855
13 202013
14 20200
15 201940
16 2019205
17 201918
18 20191
19 201949
20 201834

About David E. Leaf

David E. Leaf is a scholar working on Nephrology, Critical Care and Intensive Care Medicine and Transplantation, having authored 111 papers that have together received 4.9k indexed citations. Recurring topics across this work include Acute Kidney Injury Research (20 papers), Parathyroid Disorders and Treatments (15 papers), COVID-19 Clinical Research Studies (14 papers), Chronic Kidney Disease and Diabetes (13 papers), Dialysis and Renal Disease Management (9 papers), Cancer Immunotherapy and Biomarkers (8 papers), Hemoglobinopathies and Related Disorders (7 papers) and Renal Transplantation Outcomes and Treatments (6 papers). The work is most often cited by research in Nephrology (1.3k citations), Internal Medicine (254 citations) and Infectious Diseases (985 citations). David E. Leaf has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include David S. Goldfarb, Sushrut S. Waikar, Miguel A. Hernán, Wei Wang, Shruti Gupta, Marta Christov, Hanny Al‐Samkari, Pavan K. Bendapudi, David J. Kuter and Anem Waheed. Their work appears in journals such as Journal of the American Society of Nephrology, Clinical Journal of the American Society of Nephrology, Kidney International, American Journal of Kidney Diseases and Journal of Clinical Medicine.

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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