Kun Liao

901 citations
20 papers · 613 indexed · h-index 11
Topics
Thyroid and Parathyroid Surgery (4 papers)Nutrition and Health in Aging (4 papers)Parathyroid Disorders and Treatments (3 papers)
Partner nations
ChinaUnited StatesIndia

In The Last Decade

Kun Liao

18 papers receiving 571 citations

Peers

Kun Liao
Comparison fields: 5 of 54
  • Pathology and Forensic Medicine 362
  • Cancer Research 257
  • Surgery 134
  • Neurology 112
  • Endocrinology, Diabetes and Metabolism 100
Replace Gyula Szegedi with:
Gyula Szegedi Hungary
Carney Ja United States
Olaf Myhre‐Jensen Denmark
Gérard Abadjian Lebanon
Ayse Anil Timur United States
Katherine M. Jasnosz United States
Saverio Alvaro Italy
Patsy S. Soon Australia
S Garancini Italy
Ben Ponvilawan United States
Kun Liao relative to Gyula Szegedi Hungary Gyula Szegedi's profile →
Citations per field
00.5×10×16.1×
Gyula Szegedi · 1×
Citations per year

Countries citing papers authored by Kun Liao

Since Specialization
Citations

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

Fields of papers citing papers by Kun Liao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Liao

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Liao. A scholar is included among the top collaborators of Kun Liao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kun Liao. Kun Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 3
5 1
6
Correlation of visceral fat area and sarcopenia in patient with type 2 diabetes
1
7 5
8 27
9 11
10 16
11 12
12 32
13 30
14 34
15 1
16
The Relationship of Red Blood Cell Iron and Serum Iron with Malonate Dia-aldehyde,Superoxide Disimutase and Insulin Resistance in Cerebral Infarction Patients
1
17 10
18 358
19 39
20 31

About Kun Liao

Kun Liao is a scholar working on Nephrology, Geriatrics and Gerontology and Endocrinology, Diabetes and Metabolism, having authored 20 papers that have together received 613 indexed citations. Recurring topics across this work include Thyroid and Parathyroid Surgery (4 papers), Nutrition and Health in Aging (4 papers) and Parathyroid Disorders and Treatments (3 papers). The work is most often cited by research in Pathology and Forensic Medicine (362 citations), Cancer Research (257 citations) and Genetics (86 citations). Kun Liao has collaborated with scholars based in China, United States and India. Frequent co-authors include Charles L. Wiseman, Khosrow Daneshbod, Hao Jin, Min Cui, Juan Rosaí, Wei Li, Qingfeng Cheng, Qifu Li, Shumin Yang and Ping Yang. Their work appears in journals such as Nature Cell Biology, Cancer and Scientific Reports.

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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