Zhichao Zuo: h-index, Total Citations, and Citation Map
Zhichao Zuo's h-index is 14 (23 i10-index, 622+ total citations across 78+ publications) according to Google Scholar as of May 2026. Zhichao Zuo is affiliated with Xiangtan University.
Zhichao Zuo is a researcher affiliated with Xiangtan University, specializing in Radiology, Oncology, Medical statistics. Their work has been cited 622 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Zhichao Zuo's Citation Metrics
Bibliometric impact based on 78 indexed publications.
- H-Index
- 14
- i10-Index
- 23
- Total Citations
- 622
- Citing Countries
- 21
As of May 2026.
Zhichao Zuo has an h-index of 14 and 622 total citations across 78 publications, with research cited by institutions in 21 countries.
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Global Impact Map
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Top Cited Works
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Survival Nomogram for Stage IB Non-Small-Cell Lung Cancer Patients, Based on the SEER Database and an External Validation Cohort: Zuo et al.
2021108
Top Citing Countries
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.
229 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed a novel framework combining MRI morphological features, radiomics, and deep learning to predict lymphovascular invasion in breast cancer, establishing a reproducible methodology for non-invasive biomarker assessment.
The researcher developed a validated survival nomogram for Stage IB non-small-cell lung cancer, establishing a framework for prognostic modeling that subsequent work extended to heterogeneity scoring and machine learning applications.
The researcher developed a framework for assessing pure ground-glass nodules using deep learning and intratumoral heterogeneity to predict pulmonary adenocarcinoma invasiveness.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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