Arunashis Sau: h-index, Total Citations, and Citation Map
Arunashis Sau's h-index is 16 (23 i10-index, 771+ total citations across 4+ publications) according to Google Scholar as of May 2026. Arunashis Sau is affiliated with Imperial College London.
Arunashis Sau is a researcher affiliated with Imperial College London, specializing in Cardiac Electrophysiology. Their work has been cited 771 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Arunashis Sau's Citation Metrics
Bibliometric impact based on 4 indexed publications. Of these, 3 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 16
- i10-Index
- 23
- Total Citations
- 771
- Citing Countries
- 20
As of May 2026.
Arunashis Sau has an h-index of 16 and 771 total citations across 4 publications, with research cited by institutions in 20 countries.
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Top Cited Works
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Artificial intelligence-enabled electrocardiogram for mortality and cardiovascular risk estimation: a model development and validation study
202475
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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 fully automated deep learning algorithm for digitizing paper ECGs, enabling efficient conversion of analog records into digital formats for modern analysis.
The researcher established obesity as a significant risk factor for cardiac arrhythmias, a finding that has garnered substantial independent scholarly attention.
The researcher developed and validated an AI-enabled electrocardiogram model for estimating mortality and cardiovascular risk, establishing a significant methodological advance in digital health diagnostics.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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