Jing Xia

2.0k citations
40 papers · 1.5k · h-index 15

Impact in

Papers in

Jing Xia

38 papers receiving 1.5k citations

Peers

Jing Xia
Comparison fields: 5 of 149
  • Reproductive Medicine 329
  • Physiology 289
  • Health Information Management 38
  • Endocrinology, Diabetes and Metabolism 120
  • Public Health, Environmental and Occupational Health 198
Replace Satya Prakash Yadav with:
Satya Prakash Yadav India
Attila Gyenesei Hungary
Jie Pan China
Yixuan Fan China
Gaurav Bhatia United States
Debbie Rankin United Kingdom
Yongjie Xu China
Zhigang Wang China
Doulaye Dembélé France
Tingting He China
Jing Xia relative to Satya Prakash Yadav India Satya Prakash Yadav's profile →
Citations per field
00.5×7.0×
Satya Prakash Yadav · 1×
Citations per year

Countries citing papers authored by Jing Xia

Since Specialization
Citations

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

Fields of papers citing papers by Jing Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995426
2 2018132
3 2009129
4 1999117
5 199997
6 201788
7 201281
8 199880
9 199971
10 201646
11 201636
12 201927
13 201623
14 201820
15 201518
16 201013
17 201713
18 200910
19 19898
20 20027

About Jing Xia

Jing Xia is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Information Systems and Epidemiology, having authored 40 papers that have together received 1.5k indexed citations. Recurring topics across this work include Data Visualization and Analytics (8 papers), Face and Expression Recognition (3 papers), Adipose Tissue and Metabolism (3 papers), Artificial Intelligence in Healthcare (3 papers), Video Analysis and Summarization (3 papers), Data Mining Algorithms and Applications (3 papers), Machine Learning in Healthcare (3 papers) and Machine Learning and Data Classification (3 papers). The work is most often cited by research in Reproductive Medicine (329 citations), Physiology (289 citations), Health Information Management (38 citations), Endocrinology, Diabetes and Metabolism (120 citations) and Public Health, Environmental and Occupational Health (198 citations). Jing Xia has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Esther Schenker, Andrea Dunaif, Patrick Schrauwen, Éric Ravussin, Jing Yan, Guolong Cai, Gangmin Ning, Molei Yan, Min Zhu and Richard E. Pratley. Their work appears in journals such as International Journal of Obesity, Diabetes, IEEE Computer Graphics and Applications, Clinical Breast Cancer and Genes Brain & Behavior.

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.

Explore authors with similar magnitude of impact