Daniel Zelterman

12.6k citations
192 papers · 7.4k indexed · 2 hit papers · h-index 44

Daniel Zelterman

185 papers receiving 7.1k citations

Hit Papers

Early Assessme...3171984202619982012250500750

Peers

Daniel Zelterman
Comparison fields: 5 of 225
  • Statistics and Probability 626
  • Otorhinolaryngology 324
  • Oncology 1.5k
  • Cancer Research 726
  • Pulmonary and Respiratory Medicine 1.2k
Replace Martin Krzywinski with:
Martin Krzywinski Canada
Mary J. Lindstrom United States
Georg Heinze Austria
Michael A. Newton United States
Ying Lü United States
Hans C. van Houwelingen Netherlands
Debashis Ghosh United States
Rob Tibshirani United States
Inke R. König Germany
Jason H. Moore United States
Daniel Zelterman relative to Martin Krzywinski Canada Martin Krzywinski's profile →
Citations per field
00.5×4.3×
Martin Krzywinski · 1×
Citations per year

Countries citing papers authored by Daniel Zelterman

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Zelterman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Daniel Zelterman, 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 Daniel Zelterman Line = papers co-authored together Daniel Zelterman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202321
2 20227
3 20217
4 2019103
5 201938
6
Early Assessment of Lung Cancer Immunotherapy Response via Circulating Tumor DNAbreakdown →
2018317
7 201723
8 201415
9 2011101
10 201017
11 2009101
12 200411
13 200356
14
The use of the L-plastin promoter for adenoviral-mediated, tumor-specific gene expression in ovarian and bladder cancer cell lines.
200150
15
ACT/DB: A Clinical Trials Database Being Refined on a Pilot Basis at Two Medical Centers
19981
16 199735
17 199515
18 199317
19
Information, discrimination and divergence in cytology. III. Optimization of classification of Papanicolaou smears.
19911
20 198836

About Daniel Zelterman

Daniel Zelterman is a scholar working on Statistics and Probability, Otorhinolaryngology and Oncology, having authored 192 papers that have together received 7.4k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (21 papers), Statistical Methods in Clinical Trials (19 papers), Bayesian Methods and Mixture Models (17 papers), Statistical Methods and Inference (15 papers), Lung Cancer Treatments and Mutations (12 papers), Cancer Genomics and Diagnostics (11 papers), Cancer Immunotherapy and Biomarkers (9 papers) and Optimal Experimental Design Methods (8 papers). The work is most often cited by research in Statistics and Probability (626 citations), Otorhinolaryngology (324 citations) and Oncology (1.5k citations). Daniel Zelterman has collaborated with scholars based in United States, Russia and Canada. Frequent co-authors include Edward R. Tufte, Michael M. Paparella, Haiqun Lin, Lynn D. Wilson, Bruce G. Haffty, Frank C. Detterbeck, Brian E. Lally, Joseph M. Colasanto, Kenneth Lange and Marcos V. Goycoolea. Their work appears in journals such as Journal of Clinical Oncology, Biometrics, Computational Statistics & Data Analysis, Technometrics and Journal of the American Statistical Association.

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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