Ryan Copping
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
- Advanced Causal Inference Techniques
Papers in
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- Statistical Methods in Clinical Trials 3
- Statistical Methods and Inference 1
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- Cancer Genomics and Diagnostics 4
- Co-authors
- Michael W. Lu (2 shared papers)Brandon Arnieri (2 shared papers)William B. Capra (2 shared papers)Samuel Whipple (2 shared papers)James Zou (5 shared papers)Ruishan Liu (5 shared papers)Shemra Rizzo (5 shared papers)Navdeep Pal (4 shared papers)
- Journals
- Nature Medicine (1 paper)Nature Machine Intelligence (1 paper)Annals of Oncology (1 paper)Nature Communications (1 paper)The AAPS Journal (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Ryan Copping
9 papers receiving 424 citations
Ryan Copping's Hit Papers
Peers
Comparison fields: 5 of 84
- Health Informatics 64
- Statistics and Probability 98
- Cancer Research 58
- Economics and Econometrics 75
- Health Information Management 12
Countries citing papers authored by Ryan Copping
This map shows the geographic impact of Ryan Copping'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 Ryan Copping with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Copping more than expected).
Fields of papers citing papers by Ryan Copping
This network shows the impact of papers produced by Ryan Copping. 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 Ryan Copping. The network helps show where Ryan Copping may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan Copping, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Evaluating eligibility criteria of oncology trials using real-world data and AI Hit paper breakdown → | 2021 | 233 |
| 2 | 2019 | 82 | |
| 3 | 2023 | 42 | |
| 4 | 2021 | 28 | |
| 5 | 2022 | 27 | |
| 6 | 2022 | 14 | |
| 7 | 2024 | 12 | |
| 8 | 2024 | 2 | |
| 9 | 2020 | 1 |
About Ryan Copping
Ryan Copping is a scholar working on Statistics and Probability, Cancer Research, Pulmonary and Respiratory Medicine, Economics and Econometrics and Public Health, Environmental and Occupational Health, having authored 9 papers that have together received 441 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (4 papers), Statistical Methods in Clinical Trials (3 papers), Lung Cancer Treatments and Mutations (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Machine Learning and Data Classification (1 paper), vaccines and immunoinformatics approaches (1 paper), Bayesian Methods and Mixture Models (1 paper) and Statistical Methods and Inference (1 paper). The work is most often cited by research in Health Informatics (64 citations), Statistics and Probability (98 citations), Cancer Research (58 citations), Economics and Econometrics (75 citations) and Health Information Management (12 citations). Ryan Copping has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Michael W. Lu, Brandon Arnieri, William B. Capra, Samuel Whipple, James Zou, Ruishan Liu, Shemra Rizzo, Navdeep Pal, Ying Lü and Arturo López Pineda. Their work appears in journals such as Nature Medicine, Nature Machine Intelligence, Annals of Oncology, Nature Communications and The AAPS Journal.
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.