Hui Nian

5.1k citations
116 papers · 3.5k · h-index 33

Impact in

Papers in

Hui Nian

108 papers receiving 3.5k citations

Peers

Hui Nian
Comparison fields: 5 of 164
  • Health Information Management 234
  • Pathology and Forensic Medicine 889
  • Pharmacology 407
  • Medical Terminology 6
  • Family Practice 51
Replace Juan P. Casas with:
Juan P. Casas United Kingdom
Jennifer G. Robinson United States
Yana Vinogradova United Kingdom
Li Zuo China
Anoop D Shah United Kingdom
Jing Chen United States
Jessica Chubak United States
Joseph Yeboah United States
Sean Coady United States
Sheldon W. Tobe Canada
Hui Nian relative to Juan P. Casas United Kingdom Juan P. Casas's profile →
Citations per field
00.5×2.9×
Juan P. Casas · 1×
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 116 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011187
2 2011178
3 2013140
4 2009136
5 2017133
6 2018131
7 2014110
8 2011102
9 2015101
10 2008100
11 201797
12 201282
13 201575
14 200969
15 202169
16 201767
17 201666
18 201666
19 201465
20 201563

About Hui Nian

Hui Nian is a scholar working on Pathology and Forensic Medicine, Surgery, Endocrinology, Diabetes and Metabolism, Pharmacology and Cardiology and Cardiovascular Medicine, having authored 116 papers that have together received 3.5k indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (28 papers), Diabetes Treatment and Management (13 papers), Cervical and Thoracic Myelopathy (13 papers), Spinal Fractures and Fixation Techniques (12 papers), Musculoskeletal pain and rehabilitation (11 papers), Blood Pressure and Hypertension Studies (6 papers), Clinical practice guidelines implementation (5 papers) and Health Systems, Economic Evaluations, Quality of Life (5 papers). The work is most often cited by research in Health Information Management (234 citations), Pathology and Forensic Medicine (889 citations), Pharmacology (407 citations), Medical Terminology (6 citations) and Family Practice (51 citations). Hui Nian has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Frank E. Harrell, Roderick H. Dashwood, Chang Yu, Nancy J. Brown, Qingxia Chen, Barbara Delage, Kevin B. Johnson, John T. Pinto, Anthony L. Asher and J. Kenneth Burkus. Their work appears in journals such as Spine, The Spine Journal, Journal of Neurosurgery Spine, Hypertension and Journal of the American Medical Informatics Association.

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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