Gene Pennello

3.2k total citations
48 papers, 1.4k citations indexed

About

Gene Pennello is a scholar working on Statistics and Probability, Economics and Econometrics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gene Pennello has authored 48 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Statistics and Probability, 15 papers in Economics and Econometrics and 13 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gene Pennello's work include Statistical Methods in Clinical Trials (22 papers), Health Systems, Economic Evaluations, Quality of Life (14 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Gene Pennello is often cited by papers focused on Statistical Methods in Clinical Trials (22 papers), Health Systems, Economic Evaluations, Quality of Life (14 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). Gene Pennello collaborates with scholars based in United States, United Kingdom and Switzerland. Gene Pennello's co-authors include S. Lori Brown, Wendie A. Berg, Michael S. Middleton, Mary Scott Soo, Laura Thompson, Scott Evans, Daniel C. Sullivan, Kyle J. Myers, Susan S. Devesa and David Raunig and has published in prestigious journals such as Journal of the American Statistical Association, Cancer and Clinical Infectious Diseases.

In The Last Decade

Gene Pennello

44 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gene Pennello United States 17 456 280 278 171 161 48 1.4k
Song Zhang United States 31 221 0.5× 456 1.6× 153 0.6× 562 3.3× 93 0.6× 120 2.5k
Hongyu Jiang United States 22 270 0.6× 126 0.5× 248 0.9× 114 0.7× 79 0.5× 103 1.6k
Gerry Gray United States 6 95 0.2× 142 0.5× 239 0.9× 139 0.8× 341 2.1× 9 1.4k
Geraldine Rauch Germany 31 440 1.0× 496 1.8× 235 0.8× 347 2.0× 141 0.9× 138 2.6k
Jillian R. Tate Australia 26 446 1.0× 604 2.2× 46 0.2× 81 0.5× 56 0.3× 57 1.9k
Ionut Bebu United States 24 150 0.3× 311 1.1× 153 0.6× 181 1.1× 65 0.4× 89 1.8k
Andrea Padoan Italy 32 241 0.5× 367 1.3× 78 0.3× 295 1.7× 40 0.2× 156 3.5k
Georgia Kollia United States 24 179 0.4× 124 0.4× 514 1.8× 139 0.8× 69 0.4× 72 2.3k
Marina Kondratovich United States 10 681 1.5× 62 0.2× 63 0.2× 129 0.8× 29 0.2× 12 1.2k
Lavinia Ferrante di Ruffano United Kingdom 13 184 0.4× 186 0.7× 40 0.1× 329 1.9× 135 0.8× 23 1.9k

Countries citing papers authored by Gene Pennello

Since Specialization
Citations

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

Fields of papers citing papers by Gene Pennello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gene Pennello

This figure shows the co-authorship network connecting the top 25 collaborators of Gene Pennello. A scholar is included among the top collaborators of Gene Pennello 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 Gene Pennello. Gene Pennello 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.
Evans, Scott, Gene Pennello, Shanshan Zhang, et al.. (2025). Intention-to-diagnose and distinct research foci in diagnostic accuracy studies. The Lancet Infectious Diseases. 25(8). e472–e481.
2.
3.
Samawi, Hani M., et al.. (2023). Net benefit of diagnostic tests for multistate diseases: an indicator variables approach. Journal of Biopharmaceutical Statistics. 33(5). 611–638. 1 indexed citations
4.
Campbell, Gregory, Telba Irony, Gene Pennello, & Laura Thompson. (2023). Bayesian Statistics for Medical Devices: Progress Since 2010. Therapeutic Innovation & Regulatory Science. 57(3). 453–463. 5 indexed citations
5.
Delfino, Jana G., Gene Pennello, Huiman X. Barnhart, et al.. (2022). Multiparametric Quantitative Imaging Biomarkers for Phenotype Classification: A Framework for Development and Validation. Academic Radiology. 30(2). 183–195. 6 indexed citations
6.
Huang, Erich P., Gene Pennello, Nandita M. deSouza, et al.. (2022). Multiparametric Quantitative Imaging in Risk Prediction: Recommendations for Data Acquisition, Technical Performance Assessment, and Model Development and Validation. Academic Radiology. 30(2). 196–214. 6 indexed citations
7.
Raunig, David, Gene Pennello, Jana G. Delfino, et al.. (2022). Multiparametric Quantitative Imaging Biomarker as a Multivariate Descriptor of Health: A Roadmap. Academic Radiology. 30(2). 159–182. 6 indexed citations
8.
Wang, Xiaofeng, Gene Pennello, Nandita M. deSouza, et al.. (2022). Multiparametric Data-driven Imaging Markers: Guidelines for Development, Application and Reporting of Model Outputs in Radiomics. Academic Radiology. 30(2). 215–229. 10 indexed citations
9.
Obuchowski, Nancy A., Erich P. Huang, Nandita M. deSouza, et al.. (2022). A Framework for Evaluating the Technical Performance of Multiparameter Quantitative Imaging Biomarkers (mp-QIBs). Academic Radiology. 30(2). 147–158. 7 indexed citations
10.
Tang, Rong & Gene Pennello. (2015). Validation of Prognostic Marker Tests: Statistical Lessons Learned From Regulatory Experience. Therapeutic Innovation & Regulatory Science. 50(2). 241–252. 1 indexed citations
11.
Evans, Scott, Daniel B. Rubin, Dean Follmann, et al.. (2015). Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR). Clinical Infectious Diseases. 61(5). 800–806. 200 indexed citations
12.
Tang, Rong, et al.. (2013). Evaluation of Heart Failure Biomarker Tests: A Survey of Statistical Considerations. Journal of Cardiovascular Translational Research. 6(4). 449–457. 9 indexed citations
13.
Westfall, Peter H., James Troendle, & Gene Pennello. (2010). Multiple McNemar Tests. Biometrics. 66(4). 1185–1191. 42 indexed citations
14.
Gallas, Brandon D., Gene Pennello, & Kyle J. Myers. (2007). Multireader multicase variance analysis for binary data. Journal of the Optical Society of America A. 24(12). B70–B70. 43 indexed citations
15.
Pennello, Gene. (2006). Duncan's k ‐Ratio Bayes Rule Approach to Multiple Comparisons: An Overview. Biometrical Journal. 49(1). 78–93. 2 indexed citations
16.
Hinman, Lois M., Huang Sm, Joseph Hackett, et al.. (2006). The drug diagnostic co-development concept paper. The Pharmacogenomics Journal. 6(6). 375–380. 60 indexed citations
17.
Brown, S. Lori & Gene Pennello. (2002). Replacement Surgery and Silicone Gel Breast Implant Rupture: Self-Report by Women after Mammoplasty. Journal of Women s Health & Gender-Based Medicine. 11(3). 255–264. 15 indexed citations
18.
Brown, S. Lori, Hesha J. Duggirala, & Gene Pennello. (2002). An association of silicone-gel breast implant rupture and fibromyalgia. Current Rheumatology Reports. 4(4). 293–298. 8 indexed citations
19.
Pennello, Gene, Susan S. Devesa, & Mitchell H. Gail. (1999). Using a Mixed Effects Model to Estimate Geographic Variation in Cancer Rates. Biometrics. 55(3). 774–781. 11 indexed citations
20.
Pennello, Gene. (1997). The k -Ratio Multiple Comparisons Bayes Rule for the Balanced Two-Way Design. Journal of the American Statistical Association. 92(438). 675–684. 3 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Song Zhang Breakdown of academic impact, for papers by Hongyu Jiang Breakdown of academic impact, for papers by Gerry Gray Breakdown of academic impact, for papers by Geraldine Rauch Breakdown of academic impact, for papers by Jillian R. Tate Breakdown of academic impact, for papers by Ionut Bebu Breakdown of academic impact, for papers by Andrea Padoan Breakdown of academic impact, for papers by Georgia Kollia Breakdown of academic impact, for papers by Marina Kondratovich Breakdown of academic impact, for papers by Lavinia Ferrante di Ruffano
Rankless by CCL
2026