Pan Huang

2.6k citations
80 papers · 1.7k indexed · 1 hit paper · h-index 26
Topics
AI in cancer detection (19 papers)Radiomics and Machine Learning in Medical Imaging (18 papers)Nutrition and Health in Aging (6 papers)
Partner nations
ChinaItalyUnited States

In The Last Decade

Pan Huang

75 papers receiving 1.7k citations

Hit Papers

Heterogeneity and plasticity of epithelial–mesenchymal tr...20232026202420252023255075

Peers

Pan Huang
Comparison fields: 5 of 162
  • Physiology 324
  • Molecular Biology 268
  • Radiology, Nuclear Medicine and Imaging 257
  • Epidemiology 253
  • Artificial Intelligence 242
Replace Jim Hokanson with:
Jim Hokanson United States
Yixin Liu China
Alberto Malovini Italy
Fang Li China
Tingting Zhu China
Chung‐Chih Lin Taiwan
Uta Dahmen Germany
Hanna Suominen Finland
Lijuan Zhang China
Shu-Fang Chen China
Pan Huang relative to Jim Hokanson United States Jim Hokanson's profile →
Citations per field
00.5×9.3×
Jim Hokanson · 1×
Citations per year

Countries citing papers authored by Pan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Pan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pan Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Pan Huang. A scholar is included among the top collaborators of Pan Huang 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 Pan Huang. Pan Huang 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 6
2 19
3 0
4 11
5 1
6 3
7 0
8 14
9 40
10 21
11 34
12 32
13 22
14 39
15 46
16 7
17 28
18 60
19 17
20
Current Status and Development Trend of Commonly Used Techniques for Preparing Infrared Absorption Coating on Copper Substrate
1

About Pan Huang

Pan Huang is a scholar working on Geriatrics and Gerontology, Aging and Radiology, Nuclear Medicine and Imaging, having authored 80 papers that have together received 1.7k indexed citations. Recurring topics across this work include AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Nutrition and Health in Aging (6 papers). The work is most often cited by research in Geriatrics and Gerontology (184 citations), Aging (37 citations) and Health Informatics (25 citations). Pan Huang has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Jianghua Zhou, Francesco Mercaldo, Antonella Santone, Jiang Wang, Sukun Tian, Xiaoli Zhou, Peng Feng, Yongxue Yang, Jiping Li and Xiaoheng Tan. Their work appears in journals such as International Journal of Molecular Sciences, IEEE Access and IEEE Transactions on Medical Imaging.

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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