Daniel Levy: h-index, Total Citations, and Citation Map
Daniel Levy's h-index is 277 (1168 i10-index, 486,848+ total citations across 3+ publications) according to Google Scholar as of May 2026. Daniel Levy is affiliated with National Heart, Lung, and Blood Institute.
Daniel Levy is a researcher affiliated with National Heart, Lung, and Blood Institute, specializing in Genetics, Genomics, Epidemiology. Their work has been cited 486,848 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Daniel Levy's Citation Metrics
Bibliometric impact based on 3 indexed publications.
- H-Index
- 277
- i10-Index
- 1168
- Total Citations
- 486,848
- Citing Countries
- 25
As of May 2026.
Daniel Levy has an h-index of 277 and 486,848 total citations across 3 publications, with research cited by institutions in 25 countries.
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We've mapped 5,000 of 486,848 citations for Daniel Levy
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Global Impact Map
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Top Cited Works
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Heart disease and stroke statistics—2017 update: a report from the American Heart Association
201751,823
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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.
The researcher developed a seminal framework for predicting coronary heart disease using risk factor categories, establishing a highly cited standard in cardiovascular epidemiology.
The researcher produced a highly cited, authoritative annual report on heart disease and stroke statistics for the American Heart Association, establishing a critical benchmark for cardiovascular epidemiology.
The researcher advanced large-scale language model capabilities through the seminal GPT-4 Technical Report, establishing a foundational benchmark for multimodal reasoning and complex task performance in AI.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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