James Tooley

575 total citations
22 papers, 342 citations indexed

About

James Tooley is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Genetics. According to data from OpenAlex, James Tooley has authored 22 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cardiology and Cardiovascular Medicine, 8 papers in Surgery and 5 papers in Genetics. Recurrent topics in James Tooley's work include ECG Monitoring and Analysis (6 papers), Cardiac Imaging and Diagnostics (4 papers) and Diabetes and associated disorders (4 papers). James Tooley is often cited by papers focused on ECG Monitoring and Analysis (6 papers), Cardiac Imaging and Diagnostics (4 papers) and Diabetes and associated disorders (4 papers). James Tooley collaborates with scholars based in United States, United Kingdom and Türkiye. James Tooley's co-authors include Kevan C. Herold, Frank Waldron-Lynch, Octavian Henegariu, Richard A. Flavell, Songyan Deng, Paula Preston‐Hurlburt, Marco Pérez, David Ouyang, Euan A. Ashley and Hua Xu and has published in prestigious journals such as Circulation, European Heart Journal and The American Journal of Cardiology.

In The Last Decade

James Tooley

19 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
James Tooley United States 10 137 129 93 85 64 22 342
Danuta Galicka-Latała Poland 8 37 0.3× 90 0.7× 95 1.0× 120 1.4× 12 0.2× 33 297
Richard Mauseth United States 10 291 2.1× 227 1.8× 252 2.7× 16 0.2× 24 0.4× 13 461
Jiexin Pan China 4 59 0.4× 40 0.3× 18 0.2× 15 0.2× 13 0.2× 5 265
Georgios Sofidis Greece 12 20 0.1× 109 0.8× 38 0.4× 136 1.6× 11 0.2× 32 337
Klaus‐Dieter Palitzsch Germany 9 36 0.3× 74 0.6× 44 0.5× 71 0.8× 23 0.4× 18 353
Shenghua Tian China 8 119 0.9× 56 0.4× 168 1.8× 28 0.3× 7 0.1× 16 408
Sorin Ioacără Romania 9 42 0.3× 51 0.4× 108 1.2× 32 0.4× 3 0.0× 27 204
Xiaohua Wang China 11 68 0.5× 67 0.5× 182 2.0× 33 0.4× 23 0.4× 18 400
Marco Dell’Aquila Italy 13 15 0.1× 53 0.4× 65 0.7× 11 0.1× 15 0.2× 27 275
L. Olson United States 12 113 0.8× 335 2.6× 99 1.1× 62 0.7× 8 0.1× 33 456

Countries citing papers authored by James Tooley

Since Specialization
Citations

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

Fields of papers citing papers by James Tooley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Tooley

This figure shows the co-authorship network connecting the top 25 collaborators of James Tooley. A scholar is included among the top collaborators of James Tooley 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 James Tooley. James Tooley 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., Neal K. Bhatia, Sabyasachi Bandyopadhyay, et al.. (2025). Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram. npj Digital Medicine. 8(1). 21–21. 2 indexed citations
2.
Schricker, Amir, et al.. (2025). Failure of Transmural Posterior Wall Isolation by Pulse Field Ablation Demonstrated With Epicardial Mapping. JACC. Clinical electrophysiology. 11(11). 2519–2521.
3.
Hughes, J. Weston, Sulaiman Somani, Pierre Elias, et al.. (2024). Simple models vs. deep learning in detecting low ejection fraction from the electrocardiogram. European Heart Journal - Digital Health. 5(4). 427–434. 2 indexed citations
4.
Sarraju, Ashish, Zahra Azizi, James Tooley, et al.. (2024). Design and Implementation of an Electronic Health Record‐Integrated Hypertension Management Application. Journal of the American Heart Association. 13(2). e030884–e030884. 2 indexed citations
5.
Hughes, J. Weston, James Tooley, Jessica Torres Soto, et al.. (2023). A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease. npj Digital Medicine. 6(1). 169–169. 28 indexed citations
6.
Tooley, James, Gregory M. Marcus, & Melvin M. Scheinman. (2023). An unruly case of atrioventricular block. Heart Rhythm. 20(9). 1337–1338.
7.
8.
Hughes, J. Weston, Neal Yuan, Bryan He, et al.. (2021). Deep learning evaluation of biomarkers from echocardiogram videos. EBioMedicine. 73. 103613–103613. 37 indexed citations
9.
Yıldırım, Özal, Ulaş Baran Baloğlu, Muhammed Talo, et al.. (2021). Deep Neural Network Trained on Surface ECG Improves Diagnostic Accuracy of Prior Myocardial Infarction Over Q Wave Analysis. 1–4. 3 indexed citations
10.
Tooley, James & Marco Pérez. (2021). Role of digital health in detection and management of atrial fibrillation. Heart. 108(11). 834–839. 6 indexed citations
11.
Rogers, Albert J., James Tooley, Neal K. Bhatia, et al.. (2020). Deep neural network trained on surface ECG improves diagnostic accuracy of prior myocardial infarction over Q wave analysis. European Heart Journal. 41(Supplement_2). 3 indexed citations
12.
Tooley, James, David Ouyang, David Hadley, et al.. (2019). Comparison of QT Interval Measurement Methods and Correction Formulas in Atrial Fibrillation. The American Journal of Cardiology. 123(11). 1822–1827. 24 indexed citations
13.
Tooley, James, et al.. (2018). Frequency and timing of short-term complications following abdominoperineal resection. Journal of Surgical Research. 231. 69–76. 15 indexed citations
14.
Jean, R, et al.. (2016). Partners in Crime: Kidney Transplantation and Seizure Disorder. Transplantation Proceedings. 48(8). 2700–2708. 2 indexed citations
15.
Tooley, James, Daniel D. Bohl, Sanjay Kulkarni, et al.. (2016). Perioperative outcomes of coronary artery bypass graft in renal transplant recipients in the United States: results from the Nationwide Inpatient Sample. Clinical Transplantation. 30(10). 1258–1263. 3 indexed citations
16.
Tooley, James, Nalini Vudattu, Jinmyung Choi, et al.. (2015). Changes in T‐cell subsets identify responders to FcR‐nonbinding anti‐CD3 mAb (teplizumab) in patients with type 1 diabetes. European Journal of Immunology. 46(1). 230–241. 52 indexed citations
17.
Tooley, James, Frank Waldron-Lynch, & Kevan C. Herold. (2012). New and future immunomodulatory therapy in type 1 diabetes. Trends in Molecular Medicine. 18(3). 173–181. 33 indexed citations
18.
Tooley, James, V.S. Khangulov, J.L. Schlessman, et al.. (2011). The 1.75 Å resolution structure of fission protein Fis1 fromSaccharomyces cerevisiaereveals elusive interactions of the autoinhibitory domain. Acta Crystallographica Section F Structural Biology and Crystallization Communications. 67(11). 1310–1315. 6 indexed citations
19.
Xu, Hua, et al.. (2010). Epidermal growth factor inhibits intestinal NHE8 expression via reducing its basal transcription. American Journal of Physiology-Cell Physiology. 299(1). C51–C57. 22 indexed citations
20.
Arthurs, Owen J., et al.. (2008). Ultrasonographic determination of neonatal spinal canal depth. Archives of Disease in Childhood Fetal & Neonatal. 93(6). F451–F454. 16 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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