Christopher Quale

727 citations
10 papers · 538 · h-index 7

Impact in

Papers in

    • Statistical Methods and Bayesian Inference 2
    • Statistical Methods and Inference 2
    • Statistical Distribution Estimation and Applications 2
    • Molecular Biology Techniques and Applications 2

Christopher Quale

10 papers receiving 523 citations

Peers

Christopher Quale
Comparison fields: 5 of 85
  • Pulmonary and Respiratory Medicine 240
  • Cancer Research 107
  • Oncology 148
  • Statistics and Probability 39
  • Pharmacy 21
Replace Markus Follmann with:
Markus Follmann Germany
H-Erich Wichmann Germany
Paul Schellhammer United States
P. McCloud Australia
Edward P. DeAntoni United States
S. Rydén Sweden
J Bruin Rugge United States
Jinani Jayasekera United States
Lucie‐Marie Scailteux France
Rachael Sorg United States
Christopher Quale relative to Markus Follmann Germany Markus Follmann's profile →
Citations per field
00.5×10×15×19.5×
Markus Follmann · 1×
Citations per year

Countries citing papers authored by Christopher Quale

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Quale

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Christopher Quale, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Christopher Quale Line = papers co-authored together Christopher Quale links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2013231
2 2005121
3 199957
4 200654
5 201030
6 199822
7 200211
8 20006
9 20065
10 20091

About Christopher Quale

Christopher Quale is a scholar working on Statistics and Probability, Molecular Biology, Pulmonary and Respiratory Medicine, Oncology and Artificial Intelligence, having authored 10 papers that have together received 538 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (2 papers), Global Cancer Incidence and Screening (2 papers), Molecular Biology Techniques and Applications (2 papers), Statistical Methods and Inference (2 papers), Statistical Distribution Estimation and Applications (2 papers), Cancer Genomics and Diagnostics (1 paper), Prostate Cancer Treatment and Research (1 paper) and Autopsy Techniques and Outcomes (1 paper). The work is most often cited by research in Pulmonary and Respiratory Medicine (240 citations), Cancer Research (107 citations), Oncology (148 citations), Statistics and Probability (39 citations) and Pharmacy (21 citations). Christopher Quale has collaborated with scholars based in United States. Frequent co-authors include Rebecca Smith‐Bindman, Dejan Knezevic, Drew Watson, Audrey D. Goddard, Eric A. Klein, Cristina Magi‐Galluzzi, Kim M. Clark-Langone, Diana B. Cherbavaz, Sara M. Falzarano and Philip Chu. Their work appears in journals such as American Journal of Epidemiology, JNCI Journal of the National Cancer Institute, BMC Genomics, Journal of Clinical Oncology and American Journal of Preventive Medicine.

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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