Chien‐Ting Pan

735 citations
35 papers · 536 · h-index 14

Impact in

Papers in

Chien‐Ting Pan

35 papers receiving 531 citations

Peers

Chien‐Ting Pan
Comparison fields: 5 of 35
  • Endocrinology, Diabetes and Metabolism 375
  • Cardiology and Cardiovascular Medicine 83
  • Nephrology 8
  • Cellular and Molecular Neuroscience 10
  • Pulmonary and Respiratory Medicine 16
Replace Alfred A. Vichot with:
Alfred A. Vichot United States
Zeng Guo Australia
M Rieu France
Naomitsu Kuwamura Japan
Chia‐Hui Chang Taiwan
Andrea Llano United Kingdom
Stephen C. Lowder United States
Katelee Barrett Mueller United States
Renata Verhovec Slovenia
Mamiko Tsugawa Japan
Chien‐Ting Pan relative to Alfred A. Vichot United States Alfred A. Vichot's profile →
Citations per field
00.5×2×3.3×
Alfred A. Vichot · 1×
Citations per year

Countries citing papers authored by Chien‐Ting Pan

Since Specialization
Citations

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

Fields of papers citing papers by Chien‐Ting Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chien‐Ting Pan. 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 Chien‐Ting Pan. The network helps show where Chien‐Ting Pan may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202071
2 201959
3 200838
4 201932
5 201932
6 201925
7 202024
8 202223
9 202021
10 202021
11 202118
12 202117
13 202217
14 202115
15 202312
16 202011
17 202111
18 202310
19 202310
20 20229

About Chien‐Ting Pan

Chien‐Ting Pan is a scholar working on Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine, Reproductive Medicine, Neurology and Infectious Diseases, having authored 35 papers that have together received 536 indexed citations. Recurring topics across this work include Hormonal Regulation and Hypertension (30 papers), Cardiovascular Health and Disease Prevention (2 papers), Pulmonary Hypertension Research and Treatments (1 paper), Blood Pressure and Hypertension Studies (1 paper), Atrial Fibrillation Management and Outcomes (1 paper), Estrogen and related hormone effects (1 paper), COVID-19 Clinical Research Studies (1 paper) and Intracerebral and Subarachnoid Hemorrhage Research (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (375 citations), Cardiology and Cardiovascular Medicine (83 citations), Nephrology (8 citations), Cellular and Molecular Neuroscience (10 citations) and Pulmonary and Respiratory Medicine (16 citations). Chien‐Ting Pan has collaborated with scholars based in Taiwan, Japan and Australia. Frequent co-authors include Yen‐Hung Lin, Zheng‐Wei Chen, Chi‐Sheng Hung, Vin‐Cent Wu, Cheng‐Hsuan Tsai, Yi‐Yao Chang, Che‐Wei Liao, Chia‐Hung Chou, Chin‐Chen Chang and Bo‐Ching Lee. Their work appears in journals such as Hypertension Research, Frontiers in Endocrinology, Therapeutic Advances in Chronic Disease, Biomedicines and Journal of the American Heart 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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