Fu‐shun Pan

540 citations
28 papers · 363 · h-index 12

Impact in

Papers in

Fu‐shun Pan

25 papers receiving 355 citations

Peers

Fu‐shun Pan
Comparison fields: 5 of 60
  • Hepatology 75
  • Pulmonary and Respiratory Medicine 120
  • Radiology, Nuclear Medicine and Imaging 79
  • Surgery 144
  • Endocrinology, Diabetes and Metabolism 43
Replace Ke Lv with:
Ke Lv China
Galia Rosen Israel
Thiago Franchi Nunes Brazil
Hyeon Seon Ahn South Korea
Shiho Tokunaga Japan
Travis R. Hallett United States
Danitza Pradelli Italy
Sumio Mukaihara Japan
Dae Yoon Kim South Korea
Anita Paisant France
Fu‐shun Pan relative to Ke Lv China Ke Lv's profile →
Citations per field
00.5×1.5×1.9×
Ke Lv · 1×
Citations per year

Countries citing papers authored by Fu‐shun Pan

Since Specialization
Citations

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

Fields of papers citing papers by Fu‐shun Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201547
2 201439
3 201636
4 201732
5 201527
6 201725
7 202020
8 201820
9 201817
10 201515
11 201313
12 201811
13 201910
14 202110
15 20167
16 20197
17 20126
18 20205
19 20205
20 20193

About Fu‐shun Pan

Fu‐shun Pan is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Oncology and Endocrinology, Diabetes and Metabolism, having authored 28 papers that have together received 363 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (5 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers), MRI in cancer diagnosis (4 papers), Venous Thromboembolism Diagnosis and Management (3 papers), Cerebrovascular and Carotid Artery Diseases (3 papers), Ultrasound Imaging and Elastography (2 papers), Head and Neck Anomalies (2 papers) and Radiation Dose and Imaging (2 papers). The work is most often cited by research in Hepatology (75 citations), Pulmonary and Respiratory Medicine (120 citations), Radiology, Nuclear Medicine and Imaging (79 citations), Surgery (144 citations) and Endocrinology, Diabetes and Metabolism (43 citations). Fu‐shun Pan has collaborated with scholars based in China and United States. Frequent co-authors include Xiaoyan Xie, Ming Xu, Wei Wang, Ming‐De Lu, Luyao Zhou, Yanling Zheng, Jinyu Liang, Jia Luo, Quanyuan Shan and Wenshuo Tian. Their work appears in journals such as Journal of Ultrasound in Medicine, European Journal of Radiology, Insights into Imaging, Blood Coagulation & Fibrinolysis and Technology in Cancer Research & Treatment.

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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