Mimi Kim

189 papers receiving 7.9k citations

Mimi Kim's Hit Papers

Predictors of Pregnancy Outcomes in Patients With Lupus 2015 · 379 citations
3790+7+14Years since publication250500750

Peers

Mimi Kim
Comparison fields: 5 of 167
  • Rheumatology 2.9k
  • Nephrology 509
  • Immunology 1.3k
  • Obstetrics and Gynecology 332
  • Hepatology 256
Replace Mark H. Wener with:
Mark H. Wener United States
Søren Jacobsen Denmark
Jeffrey M. Roseman United States
Howard Amital Israel
Karen H. Costenbader United States
Matthew J. Grainge United Kingdom
Eloísa Bonfá Brazil
Chul Ahn United States
Roberto Caporali Italy
Lene Mellemkjær Denmark
Mimi Kim relative to Mark H. Wener United States Mark H. Wener's profile →
Citations per field
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Mark H. Wener · 1×
Citations per year

Countries citing papers authored by Mimi Kim

Since Specialization
Citations

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

Fields of papers citing papers by Mimi Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mimi Kim. 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 Mimi Kim. The network helps show where Mimi Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 196 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mycophenolate Mofetil or Intravenous Cyclophosphamide for Lupus Nephritis
Hit paper breakdown →
2005838
2
Predictors of Pregnancy Outcomes in Patients With Lupus
Hit paper breakdown →
2015379
3 2012295
4 2012282
5 2008228
6 1999224
7 2008211
8 2011193
9 2004135
10 2012128
11 2009127
12 2015126
13 2006124
14 2011123
15 2012123
16 2018122
17 2009122
18 2007120
19 2009111
20 2019111

About Mimi Kim

Mimi Kim is a scholar working on Rheumatology, Oncology, Epidemiology, Statistics and Probability and Molecular Biology, having authored 196 papers that have together received 8.3k indexed citations. Recurring topics across this work include Systemic Lupus Erythematosus Research (37 papers), Statistical Methods in Clinical Trials (13 papers), Traumatic Brain Injury Research (10 papers), Advanced Causal Inference Techniques (9 papers), Cancer Risks and Factors (9 papers), Statistical Methods and Inference (7 papers), Metabolism, Diabetes, and Cancer (6 papers) and Statistical Methods and Bayesian Inference (6 papers). The work is most often cited by research in Rheumatology (2.9k citations), Nephrology (509 citations), Immunology (1.3k citations), Obstetrics and Gynecology (332 citations) and Hepatology (256 citations). Mimi Kim has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Jill P. Buyon, Michelle Petri, Joan T. Merrill, Deborah Friedman, Thomas E. Rohan, Peter Izmirly, Geoffrey C. Kabat, Carolina Llanos, Jane E. Salmon and Marta Guerra. Their work appears in journals such as Cancer Causes & Control, Statistics in Medicine, Lupus Science & Medicine, Annals of the Rheumatic Diseases and Pediatric Blood & Cancer.

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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