Peter Jüni: h-index, Total Citations, and Citation Map
Peter Jüni's h-index is 169 (576 i10-index, 363,806+ total citations across 3+ publications) according to Google Scholar as of May 2026. Peter Jüni is affiliated with Professor of Medicine and Clinical Trials, University of Oxford.
Peter Jüni is a researcher affiliated with Professor of Medicine and Clinical Trials, University of Oxford, specializing in Clinical Epidemiology, Epidemiology, Cardiology. Their work has been cited 363,806 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Peter Jüni's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 169
- i10-Index
- 576
- Total Citations
- 363,806
- Citing Countries
- 24
As of May 2026.
Peter Jüni has an h-index of 169 and 363,806 total citations across 3 publications, with research cited by institutions in 24 countries.
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We've mapped 5,000 of 363,806 citations for Peter Jüni
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Global Impact Map
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Top Cited Works
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The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials
201136,380
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Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
3 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed a seminal tool for assessing risk of bias in randomised trials, establishing a widely adopted standard for evaluating clinical trial quality.
The researcher developed ROBINS-I, a seminal tool for assessing risk of bias in non-randomised studies of interventions, establishing a critical standard for evaluating evidence quality in observational research.
The researcher developed RoB 2, a revised tool for assessing risk of bias in randomised trials, establishing a new standard for methodological rigor in clinical research evaluation.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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