Tom Riley

1.7k total citations · 2 hit papers
15 papers, 1.1k citations indexed

About

Tom Riley is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Tom Riley has authored 15 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 5 papers in Pulmonary and Respiratory Medicine and 4 papers in Surgery. Recurrent topics in Tom Riley's work include Lung Cancer Diagnosis and Treatment (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Tom Riley is often cited by papers focused on Lung Cancer Diagnosis and Treatment (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Tom Riley collaborates with scholars based in United States, Canada and Malaysia. Tom Riley's co-authors include Martin C. Tammemägi, Anil K. Chaturvedi, Hormuzd A. Katki, Gerard A. Silvestri, Neil E. Caporaso, Christine D. Berg, William G. Hocking, John Commins, Paul A. Kvale and Timothy R. Church and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and Gastroenterology.

In The Last Decade

Tom Riley

13 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Selection Criteria for Lung-Cancer Screening

2013 635 citations Martin C. Tammemägi, Hormuzd A. Katki et al. New England Journal of Medicine profile →
Targeting of Low-Dose CT Screening According to the Risk of Lung-Cancer Death

2013 379 citations Stephanie Kovalchik, Martin C. Tammemägi et al. New England Journal of Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tom Riley United States	7	881	375	311	110	72	15	1.1k
Joshua N. Mirkin United States	4	702 0.8×	282 0.8×	344 1.1×	78 0.7×	69 1.0×	6	1.0k
Chun‐Ru Chien Taiwan	17	498 0.6×	408 1.1×	222 0.7×	256 2.3×	85 1.2×	58	1.0k
Umberto Cariboni Italy	15	796 0.9×	235 0.6×	300 1.0×	129 1.2×	40 0.6×	52	1.0k
Thomas L. Riley United States	15	815 0.9×	492 1.3×	253 0.8×	199 1.8×	43 0.6×	27	1.5k
Nicholas R. Faris United States	14	477 0.5×	177 0.5×	150 0.5×	74 0.7×	50 0.7×	48	613
Barbara Galen United States	5	661 0.8×	242 0.6×	554 1.8×	60 0.5×	41 0.6×	5	1.0k
Tine Schytte Denmark	18	655 0.7×	242 0.6×	528 1.7×	68 0.6×	41 0.6×	80	1.0k
Irene Mahon United States	9	369 0.4×	172 0.5×	197 0.6×	133 1.2×	31 0.4×	12	618
Bernardo H. L. Goulart United States	14	439 0.5×	415 1.1×	116 0.4×	93 0.8×	54 0.8×	51	848

Countries citing papers authored by Tom Riley

Since Specialization

Citations

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

Fields of papers citing papers by Tom Riley

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Riley

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

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Miller, Eric A., Claire S. Zhu, Neeraj K. Saxena, et al.. (2025). Cohort Profile: The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. International Journal of Epidemiology. 54(5).

Yang, Keming, Yin Cao, Carino Gurjao, et al.. (2022). Clinical and Genomic Characterization of Interval Colorectal Cancer in 3 Prospective Cohorts. Gastroenterology. 163(6). 1522–1530.e5. 5 indexed citations

Zhu, Claire S., Paul F. Pinsky, James E. Moler, et al.. (2017). Data sharing in clinical trials: An experience with two large cancer screening trials. PLoS Medicine. 14(5). e1002304–e1002304. 6 indexed citations

Wang, Dengzhi, et al.. (2017). Estimation of Sojourn Time and Transition Probability of Lung Cancer for Smokers using the PLCO Data. Journal of Biometrics & Biostatistics. 8(4). 3 indexed citations

Gohagan, John K., Lisa H. Gren, Mona N. Fouad, et al.. (2015). Managing Multi-Center Recruitment in the PLCO Cancer Screening Trial. Reviews on Recent Clinical Trials. 10(3). 187–193. 5 indexed citations

Mabie, Jerome, Tom Riley, Pamela M. Marcus, et al.. (2015). Data Processing and Analytic Support in the PLCO Cancer Screening Trial. Reviews on Recent Clinical Trials. 10(3). 233–237. 3 indexed citations

Black, Amanda, Wen‐Yi Huang, Patrick Wright, et al.. (2015). PLCO: Evolution of an Epidemiologic Resource and Opportunities for Future Studies. Reviews on Recent Clinical Trials. 10(3). 238–245. 28 indexed citations

Saleh, Aarash, et al.. (2015). Takotsubo Cardiomyopathy Post Induction of Anesthesia. Journal of Medical Cases. 6(9). 437–439.

Marcus, Pamela M., Sheryl Ogden, Lisa H. Gren, et al.. (2014). Non-compliance with the initial screening exam visit in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Preventive Medicine. 67. 82–88. 5 indexed citations

10.

Kovalchik, Stephanie, Martin C. Tammemägi, Christine D. Berg, et al.. (2013). Targeting of Low-Dose CT Screening According to the Risk of Lung-Cancer Death. New England Journal of Medicine. 369(3). 245–254. 379 indexed citations breakdown →

11.

Tammemägi, Martin C., Hormuzd A. Katki, William G. Hocking, et al.. (2013). Selection Criteria for Lung-Cancer Screening. New England Journal of Medicine. 368(8). 728–736. 635 indexed citations breakdown →

12.

Hocking, William G., Martin C. Tammemägi, John Commins, et al.. (2013). Diagnostic evaluation following a positive lung screening chest radiograph in the Prostate, Lung, Colorectal, Ovarian (PLCO) Cancer Screening Trial. Lung Cancer. 82(2). 238–244. 9 indexed citations

13.

Katki, Hormuzd A., Stephanie Kovalchik, Martin C. Tammemägi, et al.. (2013). Variation in the efficacy of low-dose computed tomographic lung screening based on risk of lung cancer mortality in the National Lung Screening Trial.. Journal of Clinical Oncology. 31(15_suppl). 1523–1523. 1 indexed citations

14.

Riley, Tom, et al.. (2011). Current treatment of choice for chronic hepatitis C infection. Infection and Drug Resistance. 4. 11–11. 7 indexed citations

15.

Reding, Douglas, Catherine A. McCarty, Tom Riley, Tom Hickey, & William G. Hocking. (2010). Positive biopsy (bx) rates for prostate cancer (PCA) based on prostate specific antigen (PSA) grouping in a large cancer screening trial: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO).. Journal of Clinical Oncology. 28(15_suppl). 4563–4563. 8 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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