Rimma Perotte

1.1k citations
23 papers · 714 indexed · h-index 11
Topics
Machine Learning in Healthcare (6 papers)Emergency and Acute Care Studies (5 papers)Biomedical Text Mining and Ontologies (3 papers)
Journals
SHILAP Revista de lepidopterologíaAmerican Journal of Kidney DiseasesNeural Networks

In The Last Decade

Rimma Perotte

20 papers receiving 687 citations

Peers

Rimma Perotte
Comparison fields: 5 of 109
  • Artificial Intelligence 340
  • Molecular Biology 211
  • Epidemiology 138
  • Health Information Management 136
  • Cognitive Neuroscience 60
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Countries citing papers authored by Rimma Perotte

Since Specialization
Citations

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

Fields of papers citing papers by Rimma Perotte

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rimma Perotte

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 0
5 2
6
Characterization of Electronic Health Record Documentation Shortcuts: Does the use of dotphrases increase efficiency in the Emergency Department?
6
7 10
8 116
9
A principled framework for phenotyping postpartum hemorrhage across multiple levels of severity.
2
10
Deep Survival Analysis: Nonparametrics and Missingness.
6
11 16
12 8
13
Improving Emergency Department Flow: Reducing Turnaround Time for Emergent CT Scans.
28
14
Approaches for using temporal and other filters for next generation phenotype discovery.
2
15 85
16 51
17 149
18
Hierarchically Supervised Latent Dirichlet Allocation
72
19 58
20 61

About Rimma Perotte

Rimma Perotte is a scholar working on Emergency Medicine, Health Information Management and Toxicology, having authored 23 papers that have together received 714 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), Emergency and Acute Care Studies (5 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Health Information Management (136 citations), Artificial Intelligence (340 citations) and Computational Mathematics (5 citations). Rimma Perotte has collaborated with scholars based in United States, Bulgaria and Canada. Frequent co-authors include Noémie Elhadad, Frank Wood, Rimma Pivovarov, George Hripcsak, Karthik Natarajan, Nicole G. Weiskopf, David J. Albers, David K. Vawdrey, Kenneth A. Norman and Ehren L. Newman. Their work appears in journals such as SHILAP Revista de lepidopterología, American Journal of Kidney Diseases and Neural Networks.

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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