Bob Zhong
Impact in
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Statistical Methods in Clinical Trials 9
- Statistical Methods and Bayesian Inference 3
- Statistical Methods and Inference 3
- Advanced Causal Inference Techniques 3
- Co-authors
- Jun ShaoJosep TaberneroEmiliano CalvoRastislav BahledaJeffrey R. InfanteAlain C. MitaVíctor MorenoAntoîne Italiano
- Journals
- Journal of Clinical Oncology (8 papers)Journal of Biopharmaceutical Statistics (5 papers)Statistics in Medicine (2 papers)Clinical Cancer Research (1 paper)Contemporary Clinical Trials (1 paper)
- Partner nations
- United StatesSpainFrance
In The Last Decade
Bob Zhong
23 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 112
- Oncology 359
- Cancer Research 133
- Immunology 186
- Statistics and Probability 65
- Surgery 348
Countries citing papers authored by Bob Zhong
This map shows the geographic impact of Bob Zhong'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 Bob Zhong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bob Zhong more than expected).
Fields of papers citing papers by Bob Zhong
This network shows the impact of papers produced by Bob Zhong. 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 Bob Zhong. The network helps show where Bob Zhong may publish in the future.
Co-authors
The 25 scholars most cited alongside Bob Zhong, 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 | 2020 | 6 | |
| 2 | 2019 | 187 | |
| 3 | 2019 | 1 | |
| 4 | 2018 | 24 | |
| 5 | 2018 | 0 | |
| 6 | 2017 | 20 | |
| 7 | 2016 | 6 | |
| 8 | 2015 | 299 | |
| 9 | 2014 | 179 | |
| 10 | 2014 | 21 | |
| 11 | 2014 | 34 | |
| 12 | 2013 | 0 | |
| 13 | 2012 | 5 | |
| 14 | A multicenter, phase II study of infliximab plus gemcitabine in pancreatic cancer cachexia. | 2008 | 122 |
| 15 | LAST OBSERVATION ANALYSIS IN ANOVA AND ANCOVA | 2005 | 5 |
| 16 | 2003 | 199 | |
| 17 | 2003 | 6 | |
| 18 | 2002 | 4 | |
| 19 | 2002 | 2 | |
| 20 | 2000 | 8 |
About Bob Zhong
Bob Zhong is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Pulmonary and Respiratory Medicine, Oncology and Gastroenterology, having authored 25 papers that have together received 1.2k indexed citations. Recurring topics across this work include Fibroblast Growth Factor Research (10 papers), Statistical Methods in Clinical Trials (9 papers), Bladder and Urothelial Cancer Treatments (6 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers), Advanced Causal Inference Techniques (3 papers), Urinary and Genital Oncology Studies (3 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Oncology (359 citations), Cancer Research (133 citations), Immunology (186 citations), Statistics and Probability (65 citations) and Surgery (348 citations). Bob Zhong has collaborated with scholars based in United States, Spain and France. Frequent co-authors include Jun Shao, Josep Tabernero, Emiliano Calvo, Rastislav Bahleda, Jeffrey R. Infante, Alain C. Mita, Víctor Moreno, Antoîne Italiano, Kim Stuyckens and Feng Luo. Their work appears in journals such as Journal of Clinical Oncology, Journal of Biopharmaceutical Statistics, Statistics in Medicine, Clinical Cancer Research and Contemporary Clinical Trials.
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.