Roberto M. Lang

478 total citations
16 papers, 338 citations indexed

About

Roberto M. Lang is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Roberto M. Lang has authored 16 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cardiology and Cardiovascular Medicine, 10 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Roberto M. Lang's work include Cardiac Imaging and Diagnostics (10 papers), Cardiovascular Function and Risk Factors (9 papers) and Cardiac Valve Diseases and Treatments (5 papers). Roberto M. Lang is often cited by papers focused on Cardiac Imaging and Diagnostics (10 papers), Cardiovascular Function and Risk Factors (9 papers) and Cardiac Valve Diseases and Treatments (5 papers). Roberto M. Lang collaborates with scholars based in United States, France and Italy. Roberto M. Lang's co-authors include Victor Mor‐Avi, Lissa Sugeng, Kenneth M. Borow, Nadjia Kachenoura, Lynn Weinert, Jonathan B. Jaspan, Alex Neumann, Kim A. Williams, Joseph A. Lodato and Anelechi Anyanwu and has published in prestigious journals such as Journal of the American College of Cardiology, American Journal of Physiology-Heart and Circulatory Physiology and Heart.

In The Last Decade

Roberto M. Lang

16 papers receiving 330 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roberto M. Lang United States 10 268 174 78 74 60 16 338
Yukisono Suzuki Japan 9 292 1.1× 203 1.2× 99 1.3× 68 0.9× 46 0.8× 13 391
S. Sparla Italy 7 512 1.9× 276 1.6× 95 1.2× 27 0.4× 36 0.6× 9 545
Ana Lúcia Arruda Brazil 7 227 0.8× 153 0.9× 61 0.8× 48 0.6× 33 0.6× 14 313
F. Faletra Italy 9 238 0.9× 103 0.6× 92 1.2× 40 0.5× 34 0.6× 15 279
SG Ray United Kingdom 7 270 1.0× 124 0.7× 53 0.7× 18 0.2× 20 0.3× 10 303
Olaf Rødevand Norway 10 498 1.9× 290 1.7× 66 0.8× 54 0.7× 36 0.6× 17 546
Vanessa Moñivas‐Palomero Spain 5 257 1.0× 90 0.5× 95 1.2× 19 0.3× 48 0.8× 7 300
Eva Hendrich Germany 10 172 0.6× 255 1.5× 120 1.5× 50 0.7× 87 1.4× 21 320
Michaelanne Rowen United States 6 250 0.9× 234 1.3× 145 1.9× 27 0.4× 87 1.4× 10 368
Georgeanne Lammertin United States 10 301 1.1× 151 0.9× 78 1.0× 127 1.7× 22 0.4× 14 347

Countries citing papers authored by Roberto M. Lang

Since Specialization
Citations

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

Fields of papers citing papers by Roberto M. Lang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roberto M. Lang. 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 Roberto M. Lang. The network helps show where Roberto M. Lang may publish in the future.

Co-authorship network of co-authors of Roberto M. Lang

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

All Works

16 of 16 papers shown
1.
Mor‐Avi, Victor, Nadjia Kachenoura, Francesco Maffessanti, et al.. (2016). Three-dimensional quantification of myocardial perfusion during regadenoson stress computed tomography. European Journal of Radiology. 85(5). 885–892. 3 indexed citations
2.
Chikwe, Joanna, et al.. (2012). Can three-dimensional echocardiography accurately predict complexity of mitral valve repair?. European Journal of Cardio-Thoracic Surgery. 41(3). 518–524. 48 indexed citations
3.
Mor‐Avi, Victor, Joseph A. Lodato, Nadjia Kachenoura, et al.. (2012). Quantitative Three-Dimensional Evaluation of Myocardial Perfusion During Regadenoson Stress Using Multidetector Computed Tomography. Journal of Computer Assisted Tomography. 36(4). 443–449. 15 indexed citations
4.
Patel, Amit R., Joseph A. Lodato, Sonal Chandra, et al.. (2011). Detection of myocardial perfusion abnormalities using ultra-low radiation dose regadenoson stress multidetector computed tomography. Journal of cardiovascular computed tomography. 5(4). 247–254. 31 indexed citations
5.
Kachenoura, Nadjia, Victor Mor‐Avi, Frédérique Frouin, et al.. (2009). Diagnostic Value of Parametric Imaging of Left Ventricular Wall Motion From Contrast-Enhanced Echocardiograms in Patients With Poor Acoustic Windows. Journal of the American Society of Echocardiography. 22(3). 276–283. 4 indexed citations
6.
Maffessanti, Francesco, Lissa Sugeng, Masaaki Takeuchi, et al.. (2009). Feasibility of regional and global left ventricular shape analysis from real-time 3d echocardiography. PubMed. 13. 3641–3644. 1 indexed citations
7.
Bardo, Dianna M.E., et al.. (2008). Multidetector computed tomography evaluation of left ventricular volumes: Sources of error and guidelines for their minimization. Journal of cardiovascular computed tomography. 2(4). 222–230. 19 indexed citations
8.
Sonne, Carolin, Lissa Sugeng, Nozomi Watanabe, et al.. (2008). Age and body surface area dependency of mitral valve and papillary apparatus parameters: assessment by real-time three-dimensional echocardiography. European Journal of Echocardiography. 10(2). 287–294. 48 indexed citations
9.
10.
Boonchieng, Ekkarat, Jeffrey S. Soble, Karen M. Dean, Roberto M. Lang, & James Robergé. (2002). Three dimensional reconstruction of blood flow within the left ventricle: comparison of normal, dilated cardiomyopathy and reduced ejection fraction. 24. 605–608. 1 indexed citations
11.
Weinert, Lynn, et al.. (1999). Identification of Cardiac Masses and Abnormal Blood Flow Patterns with Harmonic Power Doppler Contrast Echocardiography. Journal of the American Society of Echocardiography. 12(10). 871–875. 16 indexed citations
12.
Spencer, Kirk T., et al.. (1998). Age dependency of left ventricular and left atrial diastolic variables assessed with acoustic quantification. Journal of the American College of Cardiology. 31. 423–423. 2 indexed citations
13.
Mor‐Avi, Victor, et al.. (1998). Age Dependency of Left Atrial and Left Ventricular Acoustic Quantification Waveforms for the Evaluation of Diastolic Performance in Left Ventricular Hypertrophy. Journal of the American Society of Echocardiography. 11(11). 1027–1035. 12 indexed citations
14.
Mor‐Avi, Victor, et al.. (1995). Improved quantification of left ventricular function by applying signal averaging to echocardiographic acoustic quantification. Journal of the American Society of Echocardiography. 8(5). 679–689. 25 indexed citations
15.
Borow, Kenneth M., et al.. (1990). Myocardial mechanics in young adult patients with diabetes mellitus: Effects altered load, inotropic state and dynamic exercise. Journal of the American College of Cardiology. 15(7). 1508–1517. 54 indexed citations
16.
Hansen, D. E., Kenneth M. Borow, Alexander Neumann, et al.. (1986). Effects of acute lung injury and anesthesia on left ventricular mechanics. American Journal of Physiology-Heart and Circulatory Physiology. 251(6). H1195–H1204. 9 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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