Jeffrey Froning

482 total citations
19 papers, 295 citations indexed

About

Jeffrey Froning is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Complementary and alternative medicine. According to data from OpenAlex, Jeffrey Froning has authored 19 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cardiology and Cardiovascular Medicine, 7 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Complementary and alternative medicine. Recurrent topics in Jeffrey Froning's work include ECG Monitoring and Analysis (9 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiovascular Effects of Exercise (5 papers). Jeffrey Froning is often cited by papers focused on ECG Monitoring and Analysis (9 papers), Cardiac Imaging and Diagnostics (7 papers) and Cardiovascular Effects of Exercise (5 papers). Jeffrey Froning collaborates with scholars based in United States, Hungary and Canada. Jeffrey Froning's co-authors include Victor F. Froelicher, Jonathan Myers, Kenneth G. Lehmann, Douglas J. Morrison, Ralph Shabetai, Steven Goldman, Robert Edson, C Dennis, Daniel Do and R. L. Thomas and has published in prestigious journals such as Annals of Internal Medicine, Journal of the American College of Cardiology and The American Journal of Cardiology.

In The Last Decade

Jeffrey Froning

16 papers receiving 270 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey Froning United States 9 250 151 71 32 26 19 295
Nicolae Florescu Romania 3 352 1.4× 139 0.9× 51 0.7× 13 0.4× 14 0.5× 7 380
G Morgano Italy 11 337 1.3× 130 0.9× 32 0.5× 70 2.2× 85 3.3× 23 395
Marianne Brizendine United States 10 335 1.3× 323 2.1× 62 0.9× 65 2.0× 49 1.9× 13 451
Richard D. Conant United States 8 299 1.2× 221 1.5× 59 0.8× 32 1.0× 47 1.8× 11 373
Øyunn Kleiven Norway 9 231 0.9× 102 0.7× 78 1.1× 4 0.1× 10 0.4× 22 263
Raúl Chirife Argentina 9 328 1.3× 44 0.3× 28 0.4× 55 1.7× 62 2.4× 22 384
Konrad Werys United Kingdom 12 242 1.0× 197 1.3× 13 0.2× 30 0.9× 27 1.0× 29 349
John F. Seaworth United States 9 250 1.0× 208 1.4× 16 0.2× 30 0.9× 85 3.3× 14 318
Paola Emanuela Poggio Smanio Brazil 6 125 0.5× 210 1.4× 27 0.4× 45 1.4× 34 1.3× 19 253
Sri Sundaram United States 10 262 1.0× 28 0.2× 43 0.6× 42 1.3× 98 3.8× 36 364

Countries citing papers authored by Jeffrey Froning

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey Froning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeffrey Froning

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

All Works

19 of 19 papers shown
1.
Ashley, Euan A., Attila Kardos, E. Jack, et al.. (2006). Angiotensin-Converting Enzyme Genotype Predicts Cardiac and Autonomic Responses to Prolonged Exercise. Journal of the American College of Cardiology. 48(3). 523–531. 33 indexed citations
2.
Brotherton, T., et al.. (2005). Neural net analysis of exercise ECG waveforms. 294–295.
3.
Froning, Jeffrey & Victor F. Froelicher. (2003). Computerized exercise ECG testing and measurement for optimizing the prediction of coronary artery disease. 274. 95–98. 2 indexed citations
4.
5.
Prakash, Manish, Jonathan Myers, Victor F. Froelicher, et al.. (2001). Diagnostic exercise tests on 4000 consecutive men. American Heart Journal. 142(1). 127–135. 9 indexed citations
6.
Froelicher, Victor F., Kenneth G. Lehmann, R. L. Thomas, et al.. (1998). The Electrocardiographic Exercise Test in a Population with Reduced Workup Bias: Diagnostic Performance, Computerized Interpretation, and Multivariable Prediction. Annals of Internal Medicine. 128(12_Part_1). 965–974. 126 indexed citations
7.
Lehmann, Kenneth G., Ronald Thomas, Steven Goldman, et al.. (1998). Annals of Internal Medicine The Electrocardiographic Exercise Test in a Population with Reduced Workup Bias: Diagnostic Performance, Computerized Interpretation, and Multivariable Prediction. 8 indexed citations
8.
Do, Dat, et al.. (1996). Comparison of Computerized and Standard Visual Criteria of Exercise ECG for Diagnosis of Coronary Artery Disease. Annals of Noninvasive Electrocardiology. 1(4). 430–442. 11 indexed citations
9.
Rodriguez, Michael, et al.. (1993). Improved exercise test accuracy using discriminant function analysis and “recovery ST slope”. Journal of Electrocardiology. 26(3). 207–218. 10 indexed citations
10.
Ribisl, Paul M., et al.. (1993). Comparison of computer ST criteria for diagnosis of severe coronary artery disease. The American Journal of Cardiology. 71(7). 546–551. 19 indexed citations
11.
Liu, James, et al.. (1992). Usefulness of exercise-induced ST-segment depression in the inferior leads during exercise testing as a marker for coronary artery disease. The American Journal of Cardiology. 69(4). 303–307. 32 indexed citations
12.
Moussa, Issam, Michael Rodriguez, Jeffrey Froning, & Victor F. Froelicher. (1992). Prediction of severe coronary artery disease using computerized ECG measurements and discriminant function analysis. Journal of Electrocardiology. 25. 49–58. 8 indexed citations
13.
Jánosi, András, et al.. (1992). [Comparison of ST depression and various exercise test indices in the diagnosis of coronary stenosis].. PubMed. 133(9). 523–7. 1 indexed citations
14.
Rodriguez, Michael, et al.. (1992). Improved exercise test accuracy using discriminant function analysis and “recovery ST slope”. Journal of Electrocardiology. 25. 27–27. 5 indexed citations
15.
Morris, Charles K., et al.. (1991). Comparison of the Hollenberg score, ST/HR index, and standard ST analysis for the diagnosis of coronary artery disease. Journal of the American College of Cardiology. 17(2). A192–A192. 2 indexed citations
16.
Froning, Jeffrey, et al.. (1988). Exercise ECG analysis and measurement using an expert system approach. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 161–162 vol.1.
17.
Froning, Jeffrey, et al.. (1988). A real-time data-logger system using an optical disk WORM for archiving continuous 12-lead ECG data during exercise testing. Journal of Electrocardiology. 21. S141–S148. 6 indexed citations
18.
19.
Froning, Jeffrey & Victor F. Froelicher. (1987). Detection and measurement of the P-wave and T-wave during exercise testing using combined heuristic and statistical methods.. PubMed. 20 Suppl. 145–56. 9 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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