Milan Lomsky

1.1k total citations
40 papers, 697 citations indexed

About

Milan Lomsky is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Milan Lomsky has authored 40 papers receiving a total of 697 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Cardiology and Cardiovascular Medicine and 12 papers in Surgery. Recurrent topics in Milan Lomsky's work include Cardiac Imaging and Diagnostics (19 papers), Advanced MRI Techniques and Applications (8 papers) and Advanced X-ray and CT Imaging (8 papers). Milan Lomsky is often cited by papers focused on Cardiac Imaging and Diagnostics (19 papers), Advanced MRI Techniques and Applications (8 papers) and Advanced X-ray and CT Imaging (8 papers). Milan Lomsky collaborates with scholars based in Sweden, Denmark and United Kingdom. Milan Lomsky's co-authors include Lars Edenbrandt, Peter Gjertsson, Sven‐Erik Ricksten, Sture G. Blomberg, Mattias Ohlsson, Bert Andersson, Finn Waagstein, Reza Kaboteh, Christer Drott and Håkan Emanuelsson and has published in prestigious journals such as The Lancet, Journal of the American College of Cardiology and European Heart Journal.

In The Last Decade

Milan Lomsky

40 papers receiving 667 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Milan Lomsky Sweden 15 361 289 213 199 89 40 697
Alvaro Montoya United States 19 573 1.6× 87 0.3× 470 2.2× 157 0.8× 25 0.3× 37 889
F Keith United States 14 425 1.2× 97 0.3× 579 2.7× 162 0.8× 20 0.2× 24 967
Hideyuki Wakamatsu Japan 13 65 0.2× 237 0.8× 109 0.5× 114 0.6× 86 1.0× 28 494
C.A. Visser Netherlands 14 451 1.2× 194 0.7× 225 1.1× 51 0.3× 41 0.5× 34 803
Youngtaek Hong South Korea 14 237 0.7× 184 0.6× 199 0.9× 176 0.9× 6 0.1× 50 583
Saurabh K. Chokshi United States 12 383 1.1× 133 0.5× 195 0.9× 106 0.5× 119 1.3× 21 652
Attilio Maseri United Kingdom 10 482 1.3× 482 1.7× 163 0.8× 41 0.2× 11 0.1× 12 725
M S Gotsman Israel 7 465 1.3× 356 1.2× 207 1.0× 91 0.5× 19 0.2× 22 619
Duncan McNab United Kingdom 10 226 0.6× 397 1.4× 426 2.0× 199 1.0× 16 0.2× 19 655
Oben Döven Türkiye 11 319 0.9× 159 0.6× 178 0.8× 164 0.8× 34 0.4× 36 539

Countries citing papers authored by Milan Lomsky

Since Specialization
Citations

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

Fields of papers citing papers by Milan Lomsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milan Lomsky

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Lomsky. A scholar is included among the top collaborators of Milan Lomsky 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 Milan Lomsky. Milan Lomsky 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
1.
Anand, Aseem, Michael J. Morris, Reza Kaboteh, et al.. (2015). Analytic Validation of the Automated Bone Scan Index as an Imaging Biomarker to Standardize Quantitative Changes in Bone Scans of Patients with Metastatic Prostate Cancer. Journal of Nuclear Medicine. 57(1). 41–45. 37 indexed citations
2.
Edenbrandt, Lars, et al.. (2014). Computer-aided diagnosis system outperforms scoring analysis in myocardial perfusion imaging. Journal of Nuclear Cardiology. 21(3). 416–423. 15 indexed citations
3.
Edenbrandt, Lars, Peter Höglund, Sophia Frantz, et al.. (2014). Area of ischemia assessed by physicians and software packages from myocardial perfusion scintigrams. BMC Medical Imaging. 14(1). 5–5. 6 indexed citations
4.
5.
Selimović, Nedim, Bert Andersson, Odd Bech‐Hanssen, et al.. (2013). Right ventricular ejection fraction during exercise as a predictor of mortality in patients awaiting lung transplantation: a cohort study. BMJ Open. 3(4). e002108–e002108. 11 indexed citations
6.
Gjertsson, Peter, et al.. (2011). Clinical data do not improve artificial neural network interpretation of myocardial perfusion scintigraphy. Clinical Physiology and Functional Imaging. 31(3). 240–245. 1 indexed citations
7.
Lomsky, Milan, et al.. (2011). Diagnostic evaluation of three cardiac software packages using a consecutive group of patients. EJNMMI Research. 1(1). 22–22. 14 indexed citations
8.
Sadik, May, et al.. (2010). Relation between pain and skeletal metastasis in patients with prostate or breast cancer. Clinical Physiology and Functional Imaging. 31(3). 193–195. 9 indexed citations
9.
Tägil, Kristina, J. Marving, Milan Lomsky, Birger Hesse, & Lars Edenbrandt. (2008). Use of neural networks to improve quality control of interpretations in myocardial perfusion imaging. International journal of cardiac imaging. 24(8). 841–848. 5 indexed citations
10.
Lomsky, Milan, et al.. (2008). Can Nuclear Medicine Technologists Assess Whether a Myocardial Perfusion Rest Study Is Required?. Journal of Nuclear Medicine Technology. 36(4). 181–185. 6 indexed citations
11.
Lomsky, Milan, et al.. (2008). Evaluation of a decision support system for interpretation of myocardial perfusion gated SPECT. European Journal of Nuclear Medicine and Molecular Imaging. 35(8). 1523–1529. 20 indexed citations
12.
Gjertsson, Peter, et al.. (2008). Evaluation of new automated gated-SPECT and echocardiographic methods for calculating left ventricular volumes and ejection fraction. International Journal of Cardiology. 136(2). 171–177. 2 indexed citations
13.
14.
Lomsky, Milan, et al.. (2005). A new automated method for analysis of gated‐SPECT images based on a three‐dimensional heart shaped model. Clinical Physiology and Functional Imaging. 25(4). 234–240. 25 indexed citations
15.
Tygesen, Hans, G Claes, Christer Drott, et al.. (1999). Long-term effect of endoscopic transthoracic sympathicotomy on heart rate variability and QT dispersion in severe angina pectoris. International Journal of Cardiology. 70(3). 283–292. 24 indexed citations
16.
Bergström, Petra, Lars Jacobsson, & Milan Lomsky. (1999). Measurement of lung density by photon transmission for monitoring intravascular and extravascular fluid volume changes in the lungs. Clinical Physiology. 19(6). 519–526. 1 indexed citations
17.
Wennerblom, Bertil, et al.. (1998). Effects on Heart Rate Variability of Isosorbide-5-Mononitrate and Metoprolol in Patients with Recent Onset of Angina pectoris. Cardiology. 89(2). 87–93. 4 indexed citations
18.
Tygesen, Hans, G Claes, Christer Drott, et al.. (1997). Effect of Endoscopic Transthoracic Sympathicotomy on Heart Rate Variability in Severe Angina Pectoris. The American Journal of Cardiology. 79(11). 1447–1452. 13 indexed citations
19.
Tygesen, Hans, et al.. (1995). Endoscopic transthoracic sympathicotomy for severe angina. The Lancet. 345(8942). 97–98. 50 indexed citations
20.

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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