Hui Nian

113 papers receiving 3.6k citations

Peers

Hui Nian
Comparison fields: 5 of 160
  • Health Information Management 173
  • Pathology and Forensic Medicine 460
  • Endocrinology, Diabetes and Metabolism 307
  • Geriatrics and Gerontology 54
  • Surgery 663
Replace Li Zuo with:
Li Zuo China
Evi Nagler Belgium
Jennifer G. Robinson United States
Janet E. Olson United States
Jonathan Benn United Kingdom
Meguid El Nahas United Kingdom
Kwon Wook Joo South Korea
Pietro Minuz Italy
Svati H. Shah United States
Anna Köttgen Germany
Hui Nian relative to Li Zuo China Li Zuo's profile →
Citations per field
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Citations per year

Countries citing papers authored by Hui Nian

Since Specialization
Citations

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

Fields of papers citing papers by Hui Nian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011188
2 2011180
3 2013143
4 2009137
5 2017136
6 2018135
7 2014112
8 2011103
9 2015101
10 2008100
11 201798
12 201283
13 201576
14 202172
15 200969
16 201468
17 201668
18 201767
19 201667
20 201763

About Hui Nian

Hui Nian is a scholar working on Pathology and Forensic Medicine, Surgery, Endocrinology, Diabetes and Metabolism, Molecular Biology and Cardiology and Cardiovascular Medicine, having authored 120 papers that have together received 3.6k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (17 papers), Cervical and Thoracic Myelopathy (12 papers), Diabetes Treatment and Management (9 papers), Hormonal Regulation and Hypertension (4 papers), Eicosanoids and Hypertension Pharmacology (4 papers), Clinical practice guidelines implementation (4 papers), Musculoskeletal pain and rehabilitation (4 papers) and Histone Deacetylase Inhibitors Research (4 papers). The work is most often cited by research in Health Information Management (173 citations), Pathology and Forensic Medicine (460 citations), Endocrinology, Diabetes and Metabolism (307 citations), Geriatrics and Gerontology (54 citations) and Surgery (663 citations). Hui Nian has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Frank E. Harrell, Roderick H. Dashwood, Nancy J. Brown, Chang Yu, Qingxia Chen, Barbara Delage, Kevin B. Johnson, John T. Pinto, Anthony L. Asher and Matthew F. Gornet. Their work appears in journals such as The Spine Journal, Spine, Journal of Neurosurgery Spine, Journal of the American Medical Informatics Association and Hypertension.

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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