John Maidens

755 total citations
22 papers, 336 citations indexed

About

John Maidens is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Control and Systems Engineering. According to data from OpenAlex, John Maidens has authored 22 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Cardiology and Cardiovascular Medicine and 4 papers in Control and Systems Engineering. Recurrent topics in John Maidens's work include Advanced MRI Techniques and Applications (7 papers), ECG Monitoring and Analysis (4 papers) and Advanced NMR Techniques and Applications (4 papers). John Maidens is often cited by papers focused on Advanced MRI Techniques and Applications (7 papers), ECG Monitoring and Analysis (4 papers) and Advanced NMR Techniques and Applications (4 papers). John Maidens collaborates with scholars based in United States, Canada and India. John Maidens's co-authors include Murat Arcak, Shahab Kaynama, Meeko Oishi, Guy A. Dumont, Ian M. Mitchell, Peder E. Z. Larson, Jeremy W. Gordon, Ayşe Bener, Robert Bok and Rahul Aggarwal and has published in prestigious journals such as Circulation, IEEE Transactions on Automatic Control and Automatica.

In The Last Decade

John Maidens

20 papers receiving 325 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Maidens United States 9 100 91 91 63 40 22 336
Zhenghui Zhang China 9 200 2.0× 14 0.2× 398 4.4× 10 0.2× 128 3.2× 27 693
Carlos Sing‐Long Chile 9 11 0.1× 13 0.1× 138 1.5× 20 0.3× 38 0.9× 27 401
Micol Pennacchio Italy 11 14 0.1× 20 0.2× 30 0.3× 97 1.5× 22 0.6× 24 425
Biao Qu China 15 12 0.1× 42 0.5× 27 0.3× 443 7.0× 191 4.8× 52 875
Dong Xia Hong Kong 13 10 0.1× 29 0.3× 91 1.0× 20 0.3× 31 0.8× 38 537
Feng Huang China 11 9 0.1× 3 0.0× 201 2.2× 18 0.3× 13 0.3× 38 595
Manfred Liebmann Austria 8 3 0.0× 14 0.2× 40 0.4× 32 0.5× 11 0.3× 17 371
J. Hiller Australia 7 76 0.8× 5 0.1× 206 2.3× 12 0.2× 37 0.9× 29 546
Chaung Lin Taiwan 12 17 0.2× 186 2.0× 5 0.1× 32 0.5× 56 1.4× 53 459
Jiaxi Ying Hong Kong 9 19 0.2× 9 0.1× 85 0.9× 8 0.1× 12 0.3× 27 277

Countries citing papers authored by John Maidens

Since Specialization
Citations

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

Fields of papers citing papers by John Maidens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Maidens

This figure shows the co-authorship network connecting the top 25 collaborators of John Maidens. A scholar is included among the top collaborators of John Maidens 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 John Maidens. John Maidens 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.
Guo, Ling, Gregg S. Pressman, Scott B. Marrus, et al.. (2025). Automated Detection of Reduced Ejection Fraction Using an ECG-Enabled Digital Stethoscope. JACC Advances. 4(3). 101619–101619. 3 indexed citations
2.
Prince, John, John Maidens, Daniel Barbosa, et al.. (2023). Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease. Journal of the American Heart Association. 12(20). e030377–e030377. 13 indexed citations
3.
Attia, Zachi I., Jennifer Dugan, John Maidens, et al.. (2022). Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope. European Heart Journal - Digital Health. 3(3). 373–379. 20 indexed citations
4.
Guo, Ling, Umesh Tiwari, Christine Currie, et al.. (2021). Using a machine learning algorithm to detect depressed ejection fraction from a single-lead ECG. European Heart Journal. 42(Supplement_1).
5.
Attia, Zachi I., Jennifer Dugan, John Maidens, et al.. (2019). Abstract 13447: Prospective Analysis of Utility of Signals From an Ecg-Enabled Stethoscope to Automatically Detect a Low Ejection Fraction Using Neural Network Techniques Trained From the Standard 12-Lead Ecg. Circulation. 1 indexed citations
6.
Maidens, John, et al.. (2019). Neural Network Based Spectrum Prediction in Land Mobile Radio Bands for IoT deployments. Immunotechnology. 31–36. 3 indexed citations
7.
White, Brent, et al.. (2019). Abstract 13831: Handheld Wireless Digital Phonocardiography for Machine Learning-Based Detection of Mitral Regurgitation. Circulation. 2 indexed citations
8.
Maidens, John, et al.. (2019). Experimental Results on the Impact of Memory in Neural Networks for Spectrum Prediction in Land Mobile Radio Bands. IEEE Transactions on Cognitive Communications and Networking. 6(2). 771–782. 12 indexed citations
9.
Maidens, John, Jeremy W. Gordon, Hsin-Yu Chen, et al.. (2018). Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models. IEEE Transactions on Medical Imaging. 37(12). 2603–2612. 6 indexed citations
10.
Larson, Peder E. Z., Hsin‐Yu Chen, Jeremy W. Gordon, et al.. (2018). Investigation of analysis methods for hyperpolarized 13C‐pyruvate metabolic MRI in prostate cancer patients. NMR in Biomedicine. 31(11). e3997–e3997. 73 indexed citations
11.
Palma, Francis, et al.. (2018). An Improvement to Test Case Failure Prediction in the Context of Test Case Prioritization. 80–89. 14 indexed citations
12.
Maidens, John. (2017). Optimal Control for Learning with Applications in Dynamic MRI. eScholarship (California Digital Library). 1 indexed citations
13.
Maidens, John, Axel Barrau, Silvère Bonnabel, & Murat Arcak. (2017). Symmetry reduction for dynamic programming and application to MRI. SPIRE - Sciences Po Institutional REpository. 4625–4630. 1 indexed citations
14.
Maidens, John, Jeremy W. Gordon, Murat Arcak, & Peder E. Z. Larson. (2016). Optimizing Flip Angles for Metabolic Rate Estimation in Hyperpolarized Carbon-13 MRI. IEEE Transactions on Medical Imaging. 35(11). 2403–2412. 22 indexed citations
15.
Maidens, John, Andrew Packard, & Murat Arcak. (2016). Parallel dynamic programming for optimal experiment design in nonlinear systems. 1. 2894–2899. 3 indexed citations
16.
Maidens, John, Peder E. Z. Larson, & Murat Arcak. (2015). Optimal experiment design for physiological parameter estimation using hyperpolarized carbon-13 magnetic resonance imaging. 5770–5775. 8 indexed citations
17.
Maidens, John & Murat Arcak. (2014). Trajectory-based reachability analysis of switched nonlinear systems using matrix measures. 6358–6364. 2 indexed citations
18.
Maidens, John & Michael Y. Li. (2013). Global Lyapunov functions and a hierarchical control scheme for networks of robotic agents. Zenodo (CERN European Organization for Nuclear Research). 4050–4055. 4 indexed citations
19.
20.
Kaynama, Shahab, John Maidens, Meeko Oishi, Ian M. Mitchell, & Guy A. Dumont. (2012). Computing the viability kernel using maximal reachable sets. 55–64. 32 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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