Anna M. Michałowska

744 total citations
17 papers, 493 citations indexed

About

Anna M. Michałowska is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Anna M. Michałowska has authored 17 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cardiology and Cardiovascular Medicine, 8 papers in Surgery and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Anna M. Michałowska's work include Cardiac Imaging and Diagnostics (7 papers), Coronary Interventions and Diagnostics (5 papers) and Acute Myocardial Infarction Research (4 papers). Anna M. Michałowska is often cited by papers focused on Cardiac Imaging and Diagnostics (7 papers), Coronary Interventions and Diagnostics (5 papers) and Acute Myocardial Infarction Research (4 papers). Anna M. Michałowska collaborates with scholars based in Poland, United States and Canada. Anna M. Michałowska's co-authors include Wojciech Wojakowski, Michał Tendera, Marcin Majka, Mariusz Z. Ratajczak, Andrzej Ochała, Rafał Wyderka, Magda Kucia, Katarzyna Maślankiewicz, Krystyna Kozakiewicz and Marek Król and has published in prestigious journals such as Circulation, Nature Communications and European Heart Journal.

In The Last Decade

Anna M. Michałowska

17 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna M. Michałowska Poland 8 262 205 198 147 77 17 493
Alessandra Tritarelli Italy 13 424 1.6× 206 1.0× 141 0.7× 160 1.1× 105 1.4× 18 710
Hsiang‐Yiang Jui Taiwan 9 197 0.8× 273 1.3× 276 1.4× 57 0.4× 53 0.7× 10 527
Eva Koellensperger Germany 15 132 0.5× 229 1.1× 179 0.9× 180 1.2× 66 0.9× 24 625
Felix Gramley Germany 14 143 0.5× 176 0.9× 127 0.6× 352 2.4× 51 0.7× 28 645
Rafał Wyderka Poland 6 303 1.2× 208 1.0× 204 1.0× 147 1.0× 85 1.1× 19 509
Elisa Gambini Italy 14 227 0.9× 169 0.8× 98 0.5× 98 0.7× 38 0.5× 24 430
Matthews Chacko United States 7 161 0.6× 264 1.3× 245 1.2× 152 1.0× 64 0.8× 10 512
Timothy Starosta United States 8 254 1.0× 160 0.8× 118 0.6× 145 1.0× 32 0.4× 9 466
David Zisa United States 8 196 0.7× 272 1.3× 310 1.6× 111 0.8× 56 0.7× 11 559
Teresa Mancuso Italy 12 238 0.9× 166 0.8× 58 0.3× 136 0.9× 51 0.7× 16 486

Countries citing papers authored by Anna M. Michałowska

Since Specialization
Citations

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

Fields of papers citing papers by Anna M. Michałowska

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna M. Michałowska

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

All Works

17 of 17 papers shown
1.
Zhou, Jianhang, Aakash Shanbhag, Donghee Han, et al.. (2025). Automated proximal coronary artery calcium identification using artificial intelligence: advancing cardiovascular risk assessment. European Heart Journal - Cardiovascular Imaging. 26(3). 471–480. 1 indexed citations
2.
Williams, Michelle C., Aakash Shanbhag, Jianhang Zhou, et al.. (2024). Automated vessel-specific coronary artery calcification quantification with deep learning in a large multi-centre registry. European Heart Journal - Cardiovascular Imaging. 25(7). 976–985. 9 indexed citations
3.
Miller, Robert J.H., Aditya Killekar, Aakash Shanbhag, et al.. (2024). Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography. Nature Communications. 15(1). 2747–2747. 9 indexed citations
4.
Miller, Robert J.H., Aakash Shanbhag, Anna M. Michałowska, et al.. (2024). Deep Learning–Enabled Quantification of99mTc-Pyrophosphate SPECT/CT for Cardiac Amyloidosis. Journal of Nuclear Medicine. 65(7). 1144–1150. 10 indexed citations
5.
Fuć, Paweł, et al.. (2023). Technology for manufacturing catalytic systems using a pilot line for precious metal recovery. Silniki Spalinowe/Combustion Engines. 1 indexed citations
6.
Kalińczuk, Łukasz, Zbigniew Chmielak, Maciej Dąbrowski, et al.. (2022). Prognostic value of computed tomography derived measurements of pulmonary artery diameter for long-term outcomes after transcatheter aortic valve replacement. Kardiologia Polska. 80(10). 1020–1026. 2 indexed citations
7.
Kuśmierczyk, Mariusz, et al.. (2021). Aortic dissection after the Ross procedure. Kardiologia Polska. 79(6). 702–703. 2 indexed citations
8.
Michałowska, Anna M., Jarosław B. Ćwikła, Marek Konka, et al.. (2021). Eleven-year follow-up of cardiac paraganglioma in a patient with SDHD C11X gene mutation. Kardiologia Polska. 79(11). 1276–1277. 2 indexed citations
9.
Michałowska, Anna M., Kajetan Grodecki, Adam D. Staruch, et al.. (2021). Visually Estimated RESOLVE Score Based on Coronary Computed Tomography to Predict Side Branch Occlusion in Percutaneous Bifurcation Intervention. Journal of Thoracic Imaging. 36(3). 189–196. 1 indexed citations
10.
11.
Michałowska, Anna M., et al.. (2020). Intrafamilial variability of cardiovascular abnormalities in relation to p.R460H TGFBR2 mutation. Polskie Archiwum Medycyny Wewnętrznej. 130(7-8). 676–678. 1 indexed citations
12.
Grodecki, Kajetan, Maksymilian P. Opolski, Adam D. Staruch, et al.. (2020). Comparison of Computed Tomography Angiography Versus Invasive Angiography to Assess Medina Classification in Coronary Bifurcations. The American Journal of Cardiology. 125(10). 1479–1485. 9 indexed citations
13.
Michałowska, Anna M., Paweł Tyczyński, Jerzy Pręgowski, et al.. (2019). Prevalence and Anatomic Characteristics of Single Coronary Artery Diagnosed by Computed Tomography Angiography. The American Journal of Cardiology. 124(6). 939–946. 4 indexed citations
14.
Opolski, Maksymilian P., Kajetan Grodecki, Adam D. Staruch, et al.. (2019). Accuracy of RESOLVE score derived from coronary computed tomography versus visual angiography to predict side branch occlusion in percutaneous bifurcation intervention. Journal of cardiovascular computed tomography. 14(3). 258–265. 9 indexed citations
15.
Michałowska, Anna M., Paweł Tyczyński, Mariusz Kruk, Adam Witkowski, & Ilona Michałowska. (2018). Crossing of coronary arteries. Kardiologia Polska. 76(6). 1021–1021. 1 indexed citations
16.
Wojakowski, Wojciech, Michał Tendera, Anna M. Michałowska, et al.. (2005). Mobilization of CD34+, CD117+, CXCR4+, c-met+ stem cells is correlated with left ventricular ejection fraction and plasma NT-proBNP levels in patients with acute myocardial infarction. European Heart Journal. 27(3). 283–289. 72 indexed citations
17.

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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