Jun Tai

2.1k citations
108 papers · 1.6k · h-index 22

Impact in

  • Physiology top 5%
    • Obstructive Sleep Apnea Research
    • SARS-CoV-2 detection and testing
    • Tuberculosis Research and Epidemiology
    • SARS-CoV-2 and COVID-19 Research

Papers in

Jun Tai

102 papers receiving 1.6k citations

Peers

Jun Tai
Comparison fields: 5 of 111
  • Physiology 306
  • Infectious Diseases 186
  • Otorhinolaryngology 38
  • Cancer Research 81
  • Biomedical Engineering 227
Replace Shahriar M. Salamat with:
Shahriar M. Salamat United States
Álvaro Meana Spain
Massimo Marrelli Italy
Marcia L. Usui United States
Letizia Perillo Italy
Toshio Sugahara Japan
Janice S. Lee United States
William T. Lee United States
LUCY H. Y. YOUNG United States
Vito Crincoli Italy
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Citations per field
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Shahriar M. Salamat · 1×
Citations per year

Countries citing papers authored by Jun Tai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Tai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202198
2 202085
3 202176
4 202175
5 201867
6 202363
7 202255
8 202244
9 202142
10 200941
11 201637
12 202134
13 201132
14 201932
15 201731
16 201831
17 202029
18 202228
19 201725
20 202025

About Jun Tai

Jun Tai is a scholar working on Physiology, Otorhinolaryngology, Endocrinology, Diabetes and Metabolism, Surgery and Infectious Diseases, having authored 108 papers that have together received 1.6k indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (27 papers), Thyroid Cancer Diagnosis and Treatment (11 papers), Biosensors and Analytical Detection (7 papers), Head and Neck Cancer Studies (6 papers), Head and Neck Anomalies (5 papers), Vascular Malformations and Hemangiomas (5 papers), Sleep and related disorders (4 papers) and Cancer-related molecular mechanisms research (3 papers). The work is most often cited by research in Physiology (306 citations), Infectious Diseases (186 citations), Otorhinolaryngology (38 citations), Cancer Research (81 citations) and Biomedical Engineering (227 citations). Jun Tai has collaborated with scholars based in China, Australia and Macao. Frequent co-authors include Xin Ni, Yi Wang, Shengcai Wang, Yongli Guo, Shijun Li, Xiong Zhu, Zhifei Xu, Jieqiong Li, Wentong Ge and Laurence Don Wai Luu. Their work appears in journals such as Sleep Medicine, International Journal of Pediatric Otorhinolaryngology, The Laryngoscope, Science China Life Sciences and Acta Oto-Laryngologica.

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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