Anita E. Melgaard

708 total citations · 1 hit paper
12 papers, 520 citations indexed

About

Anita E. Melgaard is a scholar working on Endocrinology, Diabetes and Metabolism, Dermatology and Surgery. According to data from OpenAlex, Anita E. Melgaard has authored 12 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Dermatology and 3 papers in Surgery. Recurrent topics in Anita E. Melgaard's work include Diabetes Management and Research (6 papers), Diabetes Treatment and Management (5 papers) and Hyperglycemia and glycemic control in critically ill and hospitalized patients (3 papers). Anita E. Melgaard is often cited by papers focused on Diabetes Management and Research (6 papers), Diabetes Treatment and Management (5 papers) and Hyperglycemia and glycemic control in critically ill and hospitalized patients (3 papers). Anita E. Melgaard collaborates with scholars based in United States, Germany and Slovenia. Anita E. Melgaard's co-authors include Mark Lebwohl, Lawrence L. Anderson, Neil A. Swanson, Brian Berman, Stephen Shumack, Stephen K. Tyring, Linda Stein Gold, Thomas Larsson, Timothy S. Bailey and Ramin Tehranchi and has published in prestigious journals such as New England Journal of Medicine, Diabetes and Metabolism.

In The Last Decade

Anita E. Melgaard

10 papers receiving 494 citations

Hit Papers

Ingenol Mebutate Gel for Actinic Keratosis 2012 2026 2016 2021 2012 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anita E. Melgaard United States 6 333 311 127 88 61 12 520
John H. Pyne Australia 10 166 0.5× 135 0.4× 110 0.9× 91 1.0× 20 0.3× 21 319
Kazuyo Kaneko United Kingdom 13 81 0.2× 51 0.2× 76 0.6× 111 1.3× 9 0.1× 21 462
Il Hong South Korea 8 112 0.3× 69 0.2× 77 0.6× 163 1.9× 9 420
Rentao Yu China 11 135 0.4× 10 0.0× 44 0.3× 81 0.9× 21 0.3× 27 362
Juan Antonio Ratón Spain 11 31 0.1× 139 0.4× 69 0.5× 49 0.6× 6 0.1× 36 347
Richard Ashton United Kingdom 8 112 0.3× 157 0.5× 19 0.1× 67 0.8× 6 0.1× 14 354
Takeshi Shigematsu Japan 10 116 0.3× 91 0.3× 33 0.3× 110 1.3× 2 0.0× 20 364
Shuangquan Yan China 12 70 0.2× 35 0.1× 29 0.2× 128 1.5× 3 0.0× 27 363
Caifeng Chen China 11 46 0.1× 29 0.1× 61 0.5× 149 1.7× 5 0.1× 24 328
Hideaki Manome Japan 10 11 0.0× 296 1.0× 37 0.3× 82 0.9× 37 0.6× 11 605

Countries citing papers authored by Anita E. Melgaard

Since Specialization
Citations

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

Fields of papers citing papers by Anita E. Melgaard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anita E. Melgaard

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

All Works

12 of 12 papers shown
2.
Heller, Simon, Tadej Battelino, Timothy S. Bailey, et al.. (2023). Integrated safety and efficacy analysis of dasiglucagon for the treatment of severe hypoglycaemia in individuals with type 1 diabetes. Diabetes Obesity and Metabolism. 25(5). 1351–1360. 1 indexed citations
3.
Tehranchi, Ramin, et al.. (2022). Dasiglucagon Effects on QTc in Healthy Volunteers: A Randomized, Placebo-Controlled, Dose-Escalation, Double-Blind Study. Current Therapeutic Research. 96. 100668–100668.
4.
6.
Battelino, Tadej, Ramin Tehranchi, Timothy S. Bailey, et al.. (2021). Dasiglucagon, a Ready-To-Use Glucagon Analog, For Rapid And Effective Treatment of Severe Hypoglycemia: a Phase 3, Randomized Controlled Trial in Children With Type 1 Diabetes. Metabolism. 116. 154507–154507. 2 indexed citations
7.
Bailey, Timothy S., et al.. (2020). 1053-P: Dasiglucagon Hypopal Autoinjector as a Fast and Effective Treatment for Severe Hypoglycemia: Results of a Phase 3 Trial. Diabetes. 69(Supplement_1). 4 indexed citations
8.
Battelino, Tadej, Ramin Tehranchi, Anita E. Melgaard, et al.. (2020). 180-OR: Dasiglucagon as a Fast and Effective Treatment for Severe Hypoglycemia in Children with Diabetes. Diabetes. 69(Supplement_1). 3 indexed citations
9.
Lebwohl, Mark, Stephen Shumack, Linda Stein Gold, et al.. (2013). Long-term Follow-up Study of Ingenol Mebutate Gel for the Treatment of Actinic Keratoses. JAMA Dermatology. 149(6). 666–666. 105 indexed citations
10.
Lebwohl, Mark, et al.. (2012). Ingenol Mebutate Gel for Actinic Keratosis. New England Journal of Medicine. 366(11). 1010–1019. 337 indexed citations breakdown →
11.
Andersen, F. Alan, et al.. (2008). The irritant potential of n‐propanol (nonanoic acid vehicle) in cumulative skin irritation: a validation study of two different human in vivo test models. Skin Research and Technology. 14(3). 277–286. 12 indexed citations
12.

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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