Tina Baykaner

2.8k total citations
83 papers, 1.3k citations indexed

About

Tina Baykaner is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Pathology and Forensic Medicine. According to data from OpenAlex, Tina Baykaner has authored 83 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Cardiology and Cardiovascular Medicine, 8 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Tina Baykaner's work include Atrial Fibrillation Management and Outcomes (48 papers), Cardiac Arrhythmias and Treatments (46 papers) and Cardiac electrophysiology and arrhythmias (40 papers). Tina Baykaner is often cited by papers focused on Atrial Fibrillation Management and Outcomes (48 papers), Cardiac Arrhythmias and Treatments (46 papers) and Cardiac electrophysiology and arrhythmias (40 papers). Tina Baykaner collaborates with scholars based in United States, United Kingdom and Germany. Tina Baykaner's co-authors include Sanjiv M. Narayan, David E. Krummen, John M. Miller, Amir Schricker, Paul Clopton, Gautam Lalani, Kalyanam Shivkumar, Paul J. Wang, Junaid Zaman and Albert J. Rogers and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Tina Baykaner

75 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tina Baykaner United States 18 1.2k 87 61 39 31 83 1.3k
Lichy Han United States 14 323 0.3× 76 0.9× 27 0.4× 78 2.0× 28 0.9× 34 529
Amir Jadidi Germany 25 1.9k 1.7× 163 1.9× 58 1.0× 58 1.5× 43 1.4× 92 2.0k
Ali Amr Germany 11 477 0.4× 71 0.8× 45 0.7× 176 4.5× 44 1.4× 23 623
Daniele Della Latta Italy 13 196 0.2× 203 2.3× 53 0.9× 48 1.2× 42 1.4× 34 451
Arjan Sammani Netherlands 13 275 0.2× 24 0.3× 28 0.5× 83 2.1× 19 0.6× 20 386
Kentaro Yoshida Japan 22 1.4k 1.2× 89 1.0× 70 1.1× 121 3.1× 27 0.9× 92 1.5k
Owen Faris United States 11 1.2k 1.0× 290 3.3× 152 2.5× 61 1.6× 123 4.0× 17 1.3k
Ilaria Gallelli Italy 7 230 0.2× 41 0.5× 34 0.6× 372 9.5× 32 1.0× 10 551
Ran Zhou China 11 314 0.3× 124 1.4× 48 0.8× 38 1.0× 44 1.4× 44 564
Milad El Haddad Belgium 18 1.5k 1.2× 57 0.7× 65 1.1× 22 0.6× 16 0.5× 64 1.5k

Countries citing papers authored by Tina Baykaner

Since Specialization
Citations

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

Fields of papers citing papers by Tina Baykaner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tina Baykaner

This figure shows the co-authorship network connecting the top 25 collaborators of Tina Baykaner. A scholar is included among the top collaborators of Tina Baykaner 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 Tina Baykaner. Tina Baykaner 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.
Rogers, Albert J., Wayne R. Giles, Tina Baykaner, et al.. (2025). Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning. Circulation Arrhythmia and Electrophysiology. 18(2). e012860–e012860. 1 indexed citations
2.
Jackevicius, Cynthia A., Rony Atoui, Bindu Bittira, et al.. (2025). Post-cardiac surgery atrial fibrillation and sex differences in clinical outcomes: a systematic review and meta-analysis. European Heart Journal Open. 5(2). oeaf033–oeaf033.
3.
Vasireddi, Sunil K., Neal K. Bhatia, Albert J. Rogers, et al.. (2025). Non-cardiac and cardiac risk for ischemic stroke in young adults: The Stanford Y-CORE (Young Cardiovascular Outcomes and Risk Evaluation) study. International Journal of Stroke. 21(1). 45–56.
4.
Albayrak, Yavuz, Daniel González, E Sun, et al.. (2025). PO-05-050 PREDICTORS OF ATRIAL FIBRILLATION IN PATIENTS ON NON-BRUTON’S TYROSINE KINASE INHIBITORS. Heart Rhythm. 22(4). S584–S585.
5.
Azizi, Zahra, Paul Clopton, Hugo De Larochellière, et al.. (2024). Engineering of Generative Artificial Intelligence and Natural Language Processing Models to Accurately Identify Arrhythmia Recurrence. Circulation Arrhythmia and Electrophysiology. 18(1). e013023–e013023. 2 indexed citations
6.
Rappel, Wouter‐Jan, et al.. (2024). Spatially Conserved Spiral Wave Activity During Human Atrial Fibrillation. Circulation Arrhythmia and Electrophysiology. 17(3). e012041–e012041. 2 indexed citations
7.
Feng, Ruibin, Fleur V.Y. Tjong, Albert J. Rogers, et al.. (2023). Segmenting computed tomograms for cardiac ablation using machine learning leveraged by domain knowledge encoding. Frontiers in Cardiovascular Medicine. 10. 1189293–1189293. 4 indexed citations
8.
Razeghi, Orod, Mahmood Alhusseini, Muhammad Fazal, et al.. (2023). Atrial fibrillation ablation outcome prediction with a machine learning fusion framework incorporating cardiac computed tomography. Journal of Cardiovascular Electrophysiology. 34(5). 1164–1174. 17 indexed citations
9.
Baykaner, Tina, Krishna Pundi, Mellanie True Hills, et al.. (2023). Design and development of a digital shared decision-making tool for stroke prevention in atrial fibrillation. JAMIA Open. 6(1). ooad003–ooad003. 4 indexed citations
10.
Tang, Siyi, Orod Razeghi, Mahmood Alhusseini, et al.. (2022). Machine Learning–Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes. Circulation Arrhythmia and Electrophysiology. 15(8). e010850–e010850. 45 indexed citations
11.
Rappel, Wouter‐Jan, David E. Krummen, Tina Baykaner, et al.. (2022). Stochastic Termination of Spiral Wave Dynamics in Cardiac Tissue. PubMed. 2. 17 indexed citations
12.
Krummen, David E., Gordon Ho, Kurt S. Hoffmayer, et al.. (2021). Electrical Substrate Ablation for Refractory Ventricular Fibrillation. Circulation Arrhythmia and Electrophysiology. 14(3). e008868–e008868. 6 indexed citations
13.
Rodrigo, Miguel, Andreu M. Climent, Ismael Hernández‐Romero, et al.. (2020). Noninvasive Assessment of Complexity of Atrial Fibrillation. Circulation Arrhythmia and Electrophysiology. 13(3). e007700–e007700. 25 indexed citations
14.
Alhusseini, Mahmood, Firas Abuzaid, Albert J. Rogers, et al.. (2020). Machine Learning to Classify Intracardiac Electrical Patterns During Atrial Fibrillation. Circulation Arrhythmia and Electrophysiology. 13(8). e008160–e008160. 40 indexed citations
15.
Rogers, Albert J., Mahmood Alhusseini, David E. Krummen, et al.. (2020). Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death. Circulation Research. 128(2). 172–184. 31 indexed citations
16.
Baykaner, Tina, et al.. (2018). Cost effectiveness of focal impulse and rotor modulation guided ablation added to pulmonary vein isolation for atrial fibrillation. Journal of Cardiovascular Electrophysiology. 29(4). 526–536. 4 indexed citations
17.
Baykaner, Tina, Junaid Zaman, Albert J. Rogers, et al.. (2017). Spatial relationship of sites for atrial fibrillation drivers and atrial tachycardia in patients with both arrhythmias. International Journal of Cardiology. 248. 188–195. 7 indexed citations
18.
19.
Narayan, Sanjiv M., Tina Baykaner, Paul Clopton, et al.. (2014). Ablation of Rotor and Focal Sources Reduces Late Recurrence of Atrial Fibrillation Compared With Trigger Ablation Alone. Journal of the American College of Cardiology. 63(17). 1761–1768. 252 indexed citations
20.
Lalani, Gautam, Amir Schricker, Tina Baykaner, David E. Krummen, & Sanjiv M. Narayan. (2013). FREQUENCY ANALYSIS OF ATRIAL ACTION POTENTIAL ALTERNANS: A SENSITIVE CLINICAL INDEX OF INDIVIDUAL PROPENSITY TO ATRIAL FIBRILLATION. Journal of the American College of Cardiology. 61(10). E407–E407. 2 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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