Ying‐Kai Fu

37 papers receiving 530 citations

Peers

Ying‐Kai Fu
Comparison fields: 5 of 100
  • Otorhinolaryngology 73
  • Obstetrics and Gynecology 44
  • Radiology, Nuclear Medicine and Imaging 78
  • Anesthesiology and Pain Medicine 15
  • Computer Vision and Pattern Recognition 60
Replace Daniel Y. F. Chung with:
Daniel Y. F. Chung United Kingdom
Jingjing Zou United States
Xinlian Liu China
Xiaofei Mo China
Hiba Omer Saudi Arabia
Sojeong Park South Korea
Hong Xiang China
Dizem Arifler United States
Luis H. Galindo United States
Weili Liu China
Ying‐Kai Fu relative to Daniel Y. F. Chung United Kingdom Daniel Y. F. Chung's profile →
Citations per field
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Daniel Y. F. Chung · 1×
Citations per year

Countries citing papers authored by Ying‐Kai Fu

Since Specialization
Citations

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

Fields of papers citing papers by Ying‐Kai Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202173
2
Defining the priority of using 18F-FDG PET for recurrent cervical cancer.
200463
3
The value of 18F-FDG PET in the detection of stage M0 carcinoma of the nasopharynx.
200555
4 200444
5 197938
6 202429
7 202025
8 198023
9 202516
10 202416
11 200915
12 202313
13 200612
14 202310
15 200810
16 202410
17 202410
18 20239
19 20219
20 20228

About Ying‐Kai Fu

Ying‐Kai Fu is a scholar working on Materials Chemistry, Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering, Anesthesiology and Pain Medicine and Radiation, having authored 39 papers that have together received 552 indexed citations. Recurring topics across this work include Luminescence Properties of Advanced Materials (10 papers), Perovskite Materials and Applications (5 papers), Radiation Detection and Scintillator Technologies (4 papers), Radiation Effects and Dosimetry (4 papers), Pain Management and Opioid Use (4 papers), Glass properties and applications (3 papers), Medical Imaging Techniques and Applications (3 papers) and Video Surveillance and Tracking Methods (3 papers). The work is most often cited by research in Otorhinolaryngology (73 citations), Obstetrics and Gynecology (44 citations), Radiology, Nuclear Medicine and Imaging (78 citations), Anesthesiology and Pain Medicine (15 citations) and Computer Vision and Pattern Recognition (60 citations). Ying‐Kai Fu has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Bo Dong, Yu-Chen Chang, Baocai Yin, Xin Yang, Wuu‐Jyh Lin, Jiqing Zhang, Tzu‐Chen Yen, Xiaopeng Wei, Morton W. Miller and Christopher S. Lange. Their work appears in journals such as Innovation in Aging, European Journal of Nuclear Medicine and Molecular Imaging, Ceramics International, BioMed Research International and International Journal of Computer Vision.

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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