Chao An

1.3k citations
111 papers · 951 · h-index 18

Impact in

Papers in

    • Hepatocellular Carcinoma Treatment and Prognosis 55
    • Cholangiocarcinoma and Gallbladder Cancer Studies 3

Chao An

98 papers receiving 942 citations

Peers

Chao An
Comparison fields: 5 of 125
  • Hepatology 390
  • Radiology, Nuclear Medicine and Imaging 109
  • Health Informatics 6
  • Oncology 99
  • Pulmonary and Respiratory Medicine 111
Replace Ja‐Der Liang with:
Ja‐Der Liang Taiwan
Francesco Monti Italy
Chih‐Wei Yu Taiwan
Yuqiang Cheng China
Antoine Scherrer France
Yuefeng Ma China
Chang‐Min Kim South Korea
Alain Renault France
Cenk Sökmensüer Türkiye
Chao An relative to Ja‐Der Liang Taiwan Ja‐Der Liang's profile →
Citations per field
00.5×5.7×
Ja‐Der Liang · 1×
Citations per year

Countries citing papers authored by Chao An

Since Specialization
Citations

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

Fields of papers citing papers by Chao An

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202154
2 202144
3 201838
4 201329
5 202327
6 202127
7 202026
8 202025
9 201924
10 201523
11 202221
12 202020
13 201720
14 201819
15 202019
16 201919
17 201918
18 201717
19 202216
20 202115

About Chao An

Chao An is a scholar working on Hepatology, Surgery, Pulmonary and Respiratory Medicine, Epidemiology and Artificial Intelligence, having authored 111 papers that have together received 951 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (55 papers), Employment, Labor, and Gender Studies (7 papers), Liver Disease Diagnosis and Treatment (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Expert finding and Q&A systems (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers), Topic Modeling (3 papers) and Image Enhancement Techniques (3 papers). The work is most often cited by research in Hepatology (390 citations), Radiology, Nuclear Medicine and Imaging (109 citations), Health Informatics (6 citations), Oncology (99 citations) and Pulmonary and Respiratory Medicine (111 citations). Chao An has collaborated with scholars based in China, United States and Ethiopia. Frequent co-authors include Jie Yu, Ping Liang, Mengxuan Zuo, Fangyi Liu, Xiaoling Yu, Zhigang Cheng, Zhimei Huang, Jinhua Huang, Peihong Wu and Xin Li. Their work appears in journals such as International Journal of Hyperthermia, European Radiology, Cancer Medicine, International Journal of Surgery and Therapeutic Advances in Medical Oncology.

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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