Ranka Ler

1.4k total citations · 1 hit paper
14 papers, 956 citations indexed

About

Ranka Ler is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Ranka Ler has authored 14 papers receiving a total of 956 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cardiology and Cardiovascular Medicine, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Surgery. Recurrent topics in Ranka Ler's work include Acute Myocardial Infarction Research (9 papers), Heart Failure Treatment and Management (5 papers) and Cardiac electrophysiology and arrhythmias (4 papers). Ranka Ler is often cited by papers focused on Acute Myocardial Infarction Research (9 papers), Heart Failure Treatment and Management (5 papers) and Cardiac electrophysiology and arrhythmias (4 papers). Ranka Ler collaborates with scholars based in United States, France and Spain. Ranka Ler's co-authors include Fred S. Apple, MaryAnn M Murakami, Lesly A. Pearce, Stephen W. Smith, Malcolm J. York, Dana B. Walker, Amy K. Saenger, Allan S. Jaffe, Sara A. Love and Michael Berger and has published in prestigious journals such as Clinical Chemistry, Clinica Chimica Acta and Clinical Biochemistry.

In The Last Decade

Ranka Ler

14 papers receiving 938 citations

Hit Papers

Determination of 19 Cardiac Troponin I and T Assay 99th P... 2012 2026 2016 2021 2012 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Determination of 19 Cardiac Troponin I and T Assay 99th Percentile Values from a Common Presumably Healthy Population
    2012 399 citations Fred S. Apple, Ranka Ler et al. Clinical Chemistry profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ranka Ler United States 13 760 303 226 97 96 14 956
Show‐Hong Duh United States 16 610 0.8× 291 1.0× 205 0.9× 136 1.4× 113 1.2× 30 972
Franca Pagani Italy 17 583 0.8× 270 0.9× 181 0.8× 77 0.8× 32 0.3× 28 865
S. Hartwiger Switzerland 6 1.1k 1.4× 571 1.9× 309 1.4× 99 1.0× 48 0.5× 7 1.3k
Benoît Lattuca France 18 640 0.8× 256 0.8× 319 1.4× 114 1.2× 69 0.7× 85 984
Berthold Stegemann United Kingdom 24 1.3k 1.7× 398 1.3× 246 1.1× 63 0.6× 40 0.4× 77 1.6k
Berit Moehring Switzerland 11 824 1.1× 457 1.5× 251 1.1× 116 1.2× 62 0.6× 15 1.0k
Silvia Masotti Italy 18 561 0.7× 149 0.5× 122 0.5× 133 1.4× 33 0.3× 46 830
Thomas Nestelberger Switzerland 15 694 0.9× 366 1.2× 223 1.0× 66 0.7× 20 0.2× 103 867
Angelo Sante Bongo Italy 14 434 0.6× 235 0.8× 219 1.0× 55 0.6× 36 0.4× 71 646
Germán Cediel Spain 18 700 0.9× 154 0.5× 216 1.0× 91 0.9× 63 0.7× 86 993

Countries citing papers authored by Ranka Ler

Since Specialization
Citations

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

Fields of papers citing papers by Ranka Ler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ranka Ler

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

All Works

14 of 14 papers shown
1.
Gunsolus, Ian L., Allan S. Jaffe, Anne Sexter, et al.. (2017). Sex-specific 99th percentiles derived from the AACC Universal Sample Bank for the Roche Gen 5 cTnT assay: Comorbidities and statistical methods influence derivation of reference limits. Clinical Biochemistry. 50(18). 1073–1077. 22 indexed citations
2.
Semenov, Alexander G, Natalia N Tamm, Fred S. Apple, et al.. (2016). Searching for a BNP standard: Glycosylated proBNP as a common calibrator enables improved comparability of commercial BNP immunoassays. Clinical Biochemistry. 50(4-5). 181–185. 13 indexed citations
3.
Saenger, Amy K., Olaia Rodríguez‐Fraga, Ranka Ler, et al.. (2016). Specificity of B-Type Natriuretic Peptide Assays: Cross-Reactivity with Different BNP, NT-proBNP, and proBNP Peptides. Clinical Chemistry. 63(1). 351–358. 57 indexed citations
4.
Sandoval, Yader, Charles A. Herzog, Sara A. Love, et al.. (2016). Prognostic Value of Serial Changes in High-Sensitivity Cardiac Troponin I and T over 3 Months Using Reference Change Values in Hemodialysis Patients. Clinical Chemistry. 62(4). 631–638. 42 indexed citations
5.
6.
La’ulu, Sonia L., Fred S. Apple, MaryAnn M Murakami, et al.. (2012). Performance characteristics of the ARCHITECT Galectin-3 assay. Clinical Biochemistry. 46(1-2). 119–122. 33 indexed citations
7.
Apple, Fred S., Ranka Ler, & MaryAnn M Murakami. (2012). Determination of 19 Cardiac Troponin I and T Assay 99th Percentile Values from a Common Presumably Healthy Population. Clinical Chemistry. 58(11). 1574–1581. 399 indexed citations breakdown →
8.
Apple, Fred S., Stephen W. Smith, Lesly A. Pearce, et al.. (2011). Myeloperoxidase Improves Risk Stratification in Patients with Ischemia and Normal Cardiac Troponin I Concentrations. Clinical Chemistry. 57(4). 603–608. 18 indexed citations
9.
La’ulu, Sonia L., et al.. (2008). Performance characteristics of the Architect® brain natriuretic peptide (BNP) assay: A two site study. Clinica Chimica Acta. 391(1-2). 102–105. 12 indexed citations
10.
Apple, Fred S., MaryAnn M Murakami, Ranka Ler, Dana B. Walker, & Malcolm J. York. (2008). Analytical Characteristics of Commercial Cardiac Troponin I and T Immunoassays in Serum from Rats, Dogs, and Monkeys with Induced Acute Myocardial Injury. Clinical Chemistry. 54(12). 1982–1989. 67 indexed citations
11.
12.
Apple, Fred S., Stephen W. Smith, Lesly A. Pearce, Ranka Ler, & MaryAnn M Murakami. (2008). Use of the Centaur TnI-Ultra Assay for Detection of Myocardial Infarction and Adverse Events in Patients Presenting With Symptoms Suggestive of Acute Coronary Syndrome. Clinical Chemistry. 54(4). 723–728. 122 indexed citations
13.
Apple, Fred S., et al.. (2007). Multiple Biomarker Use for Detection of Adverse Events in Patients Presenting with Symptoms Suggestive of Acute Coronary Syndrome. Clinical Chemistry. 53(5). 874–881. 73 indexed citations
14.
Apple, Fred S., et al.. (2006). Point-of-Care i-STAT Cardiac Troponin I for Assessment of Patients with Symptoms Suggestive of Acute Coronary Syndrome,. Clinical Chemistry. 52(2). 322–325. 52 indexed citations

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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