Ronaldo S.L. Lima

635 total citations
15 papers, 426 citations indexed

About

Ronaldo S.L. Lima is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Ronaldo S.L. Lima has authored 15 papers receiving a total of 426 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Cardiology and Cardiovascular Medicine and 3 papers in Surgery. Recurrent topics in Ronaldo S.L. Lima's work include Cardiac Imaging and Diagnostics (13 papers), Advanced MRI Techniques and Applications (5 papers) and Cardiovascular Function and Risk Factors (4 papers). Ronaldo S.L. Lima is often cited by papers focused on Cardiac Imaging and Diagnostics (13 papers), Advanced MRI Techniques and Applications (5 papers) and Cardiovascular Function and Risk Factors (4 papers). Ronaldo S.L. Lima collaborates with scholars based in Brazil, Germany and Czechia. Ronaldo S.L. Lima's co-authors include Allen R. Goode, Mir S. Siadaty, Denny D. Watson, George Beller, Habib Samady, Michael Ragosta, Andrea De Lorenzo, Ana Carolina Souza, Adriana de Jesus Soares and Thais Peclat and has published in prestigious journals such as Journal of the American College of Cardiology, The American Journal of Cardiology and International Journal of Cardiology.

In The Last Decade

Ronaldo S.L. Lima

15 papers receiving 410 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ronaldo S.L. Lima Brazil 9 342 203 151 99 21 15 426
Yundai Chen China 12 280 0.8× 185 0.9× 145 1.0× 87 0.9× 32 1.5× 38 346
Birger Wandt Sweden 14 289 0.8× 454 2.2× 66 0.4× 42 0.4× 38 1.8× 31 533
Yasuhiro Makita Japan 7 191 0.6× 354 1.7× 84 0.6× 19 0.2× 36 1.7× 12 406
Patrick S. Coleman United States 5 348 1.0× 347 1.7× 246 1.6× 50 0.5× 56 2.7× 7 557
Gustavo Gavazzoni Blume Brazil 5 184 0.5× 390 1.9× 60 0.4× 12 0.1× 31 1.5× 10 427
Adisai Buakhamsri Thailand 9 284 0.8× 680 3.3× 85 0.6× 25 0.3× 34 1.6× 15 715
Güray Öncel Türkiye 8 282 0.8× 61 0.3× 126 0.8× 192 1.9× 61 2.9× 24 359
Ferry MRJ Hersbach Netherlands 2 290 0.8× 232 1.1× 247 1.6× 28 0.3× 29 1.4× 3 363
Pavel Goykhman United States 5 240 0.7× 310 1.5× 95 0.6× 12 0.1× 25 1.2× 6 384
Baiyan Zhuang China 8 221 0.6× 288 1.4× 83 0.5× 39 0.4× 34 1.6× 16 377

Countries citing papers authored by Ronaldo S.L. Lima

Since Specialization
Citations

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

Fields of papers citing papers by Ronaldo S.L. Lima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ronaldo S.L. Lima. 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 Ronaldo S.L. Lima. The network helps show where Ronaldo S.L. Lima may publish in the future.

Co-authorship network of co-authors of Ronaldo S.L. Lima

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

All Works

15 of 15 papers shown
1.
Lorenzo, Andrea De, et al.. (2017). Prognostic Assessment of Diabetics Using Myocardial Perfusion Imaging: Diabetes Mellitus is Still a Coronary Artery Disease Equivalent. The Open Cardiovascular Medicine Journal. 11(1). 76–83. 3 indexed citations
2.
Lima, Ronaldo S.L., et al.. (2017). Prognostic value of a faster, low-radiation myocardial perfusion SPECT protocol in a CZT camera. International journal of cardiac imaging. 33(12). 2049–2056. 9 indexed citations
3.
Lorenzo, Andrea De, et al.. (2017). Clinical, scintigraphic, and angiographic predictors of oxygen pulse abnormality in patients undergoing cardiopulmonary exercise testing. Clinical Cardiology. 40(10). 914–918. 14 indexed citations
4.
Greiser, Andreas, et al.. (2016). Comparison of myocardial T1 and T2 values in 3 T with T2* in 1.5 T in patients with iron overload and controls. International Journal of Hematology. 103(5). 530–536. 13 indexed citations
5.
Lorenzo, Andrea De, et al.. (2016). “Metabolically healthy” obesity: Prevalence, clinical features and association with myocardial ischaemia. Obesity Research & Clinical Practice. 11(3). 315–323. 10 indexed citations
6.
Lorenzo, Andrea De, Thais Peclat, Ana Carolina Souza, & Ronaldo S.L. Lima. (2015). Prognostic evaluation in obese patients using a dedicated multipinhole cadmium-zinc telluride SPECT camera. International journal of cardiac imaging. 32(2). 355–361. 12 indexed citations
7.
Lorenzo, Andrea De, et al.. (2014). Influence of typical angina versus inducible myocardial ischemia in the contemporary management of stable coronary artery disease. Therapeutic Advances in Cardiovascular Disease. 8(4). 145–154. 2 indexed citations
8.
Strecker, Ralph, et al.. (2013). Artifact suppression of SSFP cine sequences at 3T using a novel automatic 3D shimming algorithm. Journal of Cardiovascular Magnetic Resonance. 15. P57–P57. 2 indexed citations
9.
Lorenzo, Andrea De, et al.. (2011). Comparison between accelerated and conventional dobutamine stress protocols for myocardial perfusion scintigraphy. International journal of cardiac imaging. 28(7). 1823–1828. 2 indexed citations
10.
Fonseca, Léa Mirian Barbosa da, Sérgio Salles Xavier, Paulo Henrique Rosado-de-Castro, et al.. (2010). Biodistribution of bone marrow mononuclear cells in chronic chagasic cardiomyopathy after intracoronary injection. International Journal of Cardiology. 149(3). 310–314. 26 indexed citations
11.
Lorenzo, Andrea De & Ronaldo S.L. Lima. (2009). Reduced Heart Rate Response to Dipyridamole as a Marker of Left Ventricular Dysfunction in Diabetic Patients Undergoing Myocardial Perfusion Scintigraphy. Clinical Nuclear Medicine. 34(5). 275–278. 4 indexed citations
12.
Lorenzo, Andrea De & Ronaldo S.L. Lima. (2008). Influence of chronic renal failure on the heart rate response to dipyridamole in patients undergoing myocardial perfusion SPECT. Journal of Nuclear Cardiology. 15(2). 193–200. 8 indexed citations
13.
Lima, Ronaldo S.L., Andrea De Lorenzo, & Adriana de Jesus Soares. (2006). Relation Between Postexercise Abnormal Heart Rate Recovery and Myocardial Damage Evidenced by Gated Single-Photon Emission Computed Tomography. The American Journal of Cardiology. 97(10). 1452–1454. 18 indexed citations
14.
Lima, Ronaldo S.L., Denny D. Watson, Allen R. Goode, et al.. (2003). Incremental value of combined perfusion and function over perfusion alone by gated SPECT myocardial perfusion imaging for detection of severe three-vessel coronary artery disease. Journal of the American College of Cardiology. 42(1). 64–70. 274 indexed citations
15.
Lima, Ronaldo S.L., et al.. (2003). Incremental prognostic value of myocardial perfusion 99m-technetium-sestamibi SPECT in the elderly. International Journal of Cardiology. 93(2-3). 137–143. 29 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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