Michael Freese

5.4k total citations · 1 hit paper
31 papers, 1.5k citations indexed

About

Michael Freese is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Michael Freese has authored 31 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cardiology and Cardiovascular Medicine, 13 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Surgery. Recurrent topics in Michael Freese's work include Acute Myocardial Infarction Research (16 papers), Cardiac Imaging and Diagnostics (13 papers) and Heart Failure Treatment and Management (9 papers). Michael Freese is often cited by papers focused on Acute Myocardial Infarction Research (16 papers), Cardiac Imaging and Diagnostics (13 papers) and Heart Failure Treatment and Management (9 papers). Michael Freese collaborates with scholars based in Switzerland, Spain and Germany. Michael Freese's co-authors include Raphael Twerenbold, Eugene R. Passamani, Harold P. Morris, Howard L. Elford, Tobias Reichlin, Claudia Stelzig, Philip Haaf, Christian Mueller, Miriam Reiter and Beatrice Drexler and has published in prestigious journals such as Journal of Biological Chemistry, Circulation and Journal of the American College of Cardiology.

In The Last Decade

Michael Freese

26 papers receiving 1.4k citations

Hit Papers

align trajectories

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.

Ribonucleotide Reductase and Cell Proliferation

1970 282 citations Michael Freese et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Freese Switzerland	13	1.1k	618	342	234	115	31	1.5k
Luigi La Vecchia Italy	21	921 0.9×	218 0.4×	328 1.0×	228 1.0×	37 0.3×	80	1.7k
Wei Fang China	21	491 0.5×	513 0.8×	207 0.6×	201 0.9×	97 0.8×	107	1.4k
Gregor Leibundgut Switzerland	22	931 0.9×	288 0.5×	881 2.6×	165 0.7×	39 0.3×	95	1.7k
Jean‐Christophe Cornily France	14	925 0.9×	527 0.9×	527 1.5×	97 0.4×	17 0.1×	24	1.7k
Peter Fries Germany	17	447 0.4×	225 0.4×	180 0.5×	77 0.3×	30 0.3×	86	1.0k
Steven L. Goldberg United States	29	2.1k 2.0×	1.3k 2.2×	2.5k 7.2×	533 2.3×	41 0.4×	86	3.9k
Ranka Ler United States	13	760 0.7×	303 0.5×	226 0.7×	97 0.4×	21 0.2×	14	956
Sanjeev Francis United States	22	962 0.9×	471 0.8×	473 1.4×	292 1.2×	208 1.8×	47	2.5k
Mark Anderson United States	24	447 0.4×	62 0.1×	996 2.9×	374 1.6×	102 0.9×	101	2.1k
R. B. A. van den Brink Netherlands	19	1.2k 1.1×	195 0.3×	393 1.1×	71 0.3×	104 0.9×	40	1.5k

Countries citing papers authored by Michael Freese

Since Specialization

Citations

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

Fields of papers citing papers by Michael Freese

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Freese

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

All Works

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20 of 20 papers shown

Schwerzmann, Markus, Judith Bouchardy, Ronny R. Buechel, et al.. (2024). Stable Longitudinal Quality of Life in the SERVE Trial Among Adults With Transposition of the Great Arteries and a Systemic Right Ventricle. PubMed. 4(2). 81–91.

Ruperti‐Repilado, Francisco Javier, Philip Haaf, Pedro López‐Ayala, et al.. (2024). NT-proBNP in systemic right ventricles: a new cutoff level for risk stratification?. Revista Española de Cardiología (English Edition). 78(2). 107–116.

Ruperti‐Repilado, Francisco Javier, Philip Haaf, Pedro López‐Ayala, et al.. (2024). Prognostic Value and Determinants of High‐Sensitivity Cardiac Troponin T in Patients With a Systemic Right Ventricle: Insights From the SERVE Trial. Journal of the American Heart Association. 13(10). e034776–e034776.

Arslani, Ketina, Otmar Pfister, Michael Freese, et al.. (2020). Choir singing improves respiratory muscle strength and quality of life in patients with structural heart disease – HeartChoir: a randomised clinical trial. Swiss Medical Weekly. 150(3738). w20346–w20346. 5 indexed citations

Tobler, Daniel, Judith Bouchardy, Dik Heg, et al.. (2017). Effect of phosphodiesterase-5 inhibition with Tadalafil on SystEmic Right VEntricular size and function – A multi-center, double-blind, randomized, placebo-controlled clinical trial – SERVE trial - Rational and design. International Journal of Cardiology. 243. 354–359. 15 indexed citations

Irfan, Affan, Raphael Twerenbold, Karin Wildi, et al.. (2015). ASSOCIATION OF ALBUMIN AND HIGH SENSITIVE CARDIAC TROPONIN T AND I LEVELS AMONG CHEST PAIN PATIENTS PRESENTING TO EMERGENCY DEPARTMENT. Journal of the American College of Cardiology. 65(10). A135–A135.

Sou, Seoung Mann, Raphael Twerenbold, Tobias Reichlin, et al.. (2014). B-type Natriuretic Peptide and Clinical Judgment in the Detection of Exercise-induced Myocardial Ischemia. The American Journal of Medicine. 127(5). 427–435. 12 indexed citations

Maeder, Micha T., Martin Brutsche, Raphael Twerenbold, et al.. (2014). Midregional pro-adrenomedullin and copeptin: exercise kinetics and association with the cardiopulmonary exercise response in comparison to B-type natriuretic peptide. European Journal of Applied Physiology. 114(4). 815–824. 10 indexed citations

Haaf, Philip, Christa Zellweger, Tobias Reichlin, et al.. (2013). Utility of C-terminal Proendothelin in the Early Diagnosis and Risk Stratification of Patients With Suspected Acute Myocardial Infarction. Canadian Journal of Cardiology. 30(2). 195–203. 4 indexed citations

10.

Haaf, Philip, Beatrice Drexler, Tobias Reichlin, et al.. (2012). High-Sensitivity Cardiac Troponin in the Distinction of Acute Myocardial Infarction From Acute Cardiac Noncoronary Artery Disease. Circulation. 126(1). 31–40. 101 indexed citations

11.

Meune, Christophe, Raphael Twerenbold, Beatrice Drexler, et al.. (2012). Midregional Pro–A-Type Natriuretic Peptide for Diagnosis and Prognosis in Patients With Suspected Acute Myocardial Infarction. The American Journal of Cardiology. 109(8). 1117–1123. 12 indexed citations

12.

Potocki, Mihael, Tobias Reichlin, Christa Zellweger, et al.. (2012). Diagnostic and prognostic impact of copeptin and high-sensitivity cardiac troponin T in patients with pre-existing coronary artery disease and suspected acute myocardial infarction. Heart. 98(7). 558–565. 65 indexed citations

13.

Meune, Christophe, Cathrin Balmelli, Raphael Twerenbold, et al.. (2012). Utility of 14 novel biomarkers in patients with acute chest pain and undetectable levels of conventional cardiac troponin. International Journal of Cardiology. 167(4). 1164–1169. 12 indexed citations

14.

Reichlin, Tobias, Christian Schindler, Beatrice Drexler, et al.. (2012). One-Hour Rule-out and Rule-in of Acute Myocardial Infarction Using High-Sensitivity Cardiac Troponin T. Archives of Internal Medicine. 172(16). 1211–1211. 357 indexed citations

15.

Irfan, Affan, Raphael Twerenbold, Miriam Reiter, et al.. (2012). Determinants of High-Sensitivity Troponin T Among Patients with a Noncardiac Cause of Chest Pain. The American Journal of Medicine. 125(5). 491–498.e1. 51 indexed citations

16.

Reichlin, Tobias, Raphael Twerenbold, Miriam Reiter, et al.. (2012). Introduction of High-sensitivity Troponin Assays: Impact on Myocardial Infarction Incidence and Prognosis. The American Journal of Medicine. 125(12). 1205–1213.e1. 141 indexed citations

17.

Haaf, Philip, Cathrin Balmelli, Tobias Reichlin, et al.. (2011). N-terminal Pro B-type Natriuretic Peptide in the Early Evaluation of Suspected Acute Myocardial Infarction. The American Journal of Medicine. 124(8). 731–739. 25 indexed citations

18.

Reiter, Miriam, Raphael Twerenbold, Tobias Reichlin, et al.. (2011). Early diagnosis of acute myocardial infarction in the elderly using more sensitive cardiac troponin assays. European Heart Journal. 32(11). 1379–1389. 201 indexed citations

19.

Meune, Christophe, Beatrice Drexler, Philip Haaf, et al.. (2011). The GRACE score's performance in predicting in-hospital and 1-year outcome in the era of high-sensitivity cardiac troponin assays and B-type natriuretic peptide. Heart. 97(18). 1479–1483. 56 indexed citations

20.

Schaub, Nora, Tobias Reichlin, Christophe Meune, et al.. (2011). Markers of Plaque Instability in the Early Diagnosis and Risk Stratification of Acute Myocardial Infarction. Clinical Chemistry. 58(1). 246–256. 47 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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