Daniel Feldman
Impact in
- Statistics and Probability top 2%
- Advanced Causal Inference Techniques
- Statistical Methods in Clinical Trials
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Family Practice top 10%
Papers in
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- Breast Cancer Treatment Studies 2
- Co-authors
- B. EfronOren M. TepperJacob G. UngerKevin SmallNolan S. KarpMihye ChoiNaveen KumarBrad Efron
- Journals
- Reviews in Cardiovascular Medicine (3 papers)Journal of the American Statistical Association (3 papers)Journal of Clinical Oncology (3 papers)Annals of Plastic Surgery (2 papers)The American Surgeon (1 paper)
- Partner nations
- United StatesItalyCanada
In The Last Decade
Daniel Feldman
24 papers receiving 606 citations
Peers
Comparison fields: 5 of 106
- Statistics and Probability 178
- Family Practice 24
- Organizational Behavior and Human Resource Management 65
- Public Administration 14
- Cancer Research 58
Countries citing papers authored by Daniel Feldman
This map shows the geographic impact of Daniel Feldman'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 Daniel Feldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Feldman more than expected).
Fields of papers citing papers by Daniel Feldman
This network shows the impact of papers produced by Daniel Feldman. 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 Daniel Feldman. The network helps show where Daniel Feldman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Feldman, 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 | 2022 | 5 | |
| 2 | 2022 | 1 | |
| 3 | 2022 | 0 | |
| 4 | 2022 | 1 | |
| 5 | 2018 | 35 | |
| 6 | 2017 | 15 | |
| 7 | 2016 | 9 | |
| 8 | 2016 | 7 | |
| 9 | 2015 | 6 | |
| 10 | 2009 | 18 | |
| 11 | 2009 | 53 | |
| 12 | 2009 | 52 | |
| 13 | 2009 | 2 | |
| 14 | 2009 | 5 | |
| 15 | 2009 | 2 | |
| 16 | 2008 | 31 | |
| 17 | 2005 | 1 | |
| 18 | 1991 | 216 | |
| 19 | Compliance as an Explanatory Variable in Clinical Trials with Comments and Rejoinder | 1991 | 1 |
| 20 | 1990 | 123 |
About Daniel Feldman
Daniel Feldman is a scholar working on Internal Medicine, Cancer Research, Cardiology and Cardiovascular Medicine, Statistics and Probability and Occupational Therapy, having authored 28 papers that have together received 644 indexed citations. Recurring topics across this work include Antiplatelet Therapy and Cardiovascular Diseases (4 papers), Coronary Interventions and Diagnostics (4 papers), Breast Implant and Reconstruction (4 papers), Cardiac and Coronary Surgery Techniques (3 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Lung Cancer Treatments and Mutations (3 papers), Reconstructive Surgery and Microvascular Techniques (3 papers) and Breast Cancer Treatment Studies (2 papers). The work is most often cited by research in Statistics and Probability (178 citations), Family Practice (24 citations), Organizational Behavior and Human Resource Management (65 citations), Public Administration (14 citations) and Cancer Research (58 citations). Daniel Feldman has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include B. Efron, Oren M. Tepper, Jacob G. Unger, Kevin Small, Nolan S. Karp, Mihye Choi, Naveen Kumar, Brad Efron, Joyce Cheung‐Flynn and Colleen M. Brophy. Their work appears in journals such as Reviews in Cardiovascular Medicine, Journal of the American Statistical Association, Journal of Clinical Oncology, Annals of Plastic Surgery and The American Surgeon.
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.