Weijing Tang

17 papers receiving 319 citations

Peers

Weijing Tang
Comparison fields: 5 of 83
  • Hepatology 70
  • Biological Psychiatry 15
  • Health Informatics 7
  • Neurology 42
  • Health Information Management 23
Replace Camilla Dalby Hansen with:
Camilla Dalby Hansen Denmark
P. F. He China
Ling Jia China
Martina Urbanek Austria
Xiaosong Xu China
R. Lieverse Netherlands
Ze Zhang China
Peipei Wang China
Jiehua Li China
Weijing Tang relative to Camilla Dalby Hansen Denmark Camilla Dalby Hansen's profile →
Citations per field
00.5×7.7×
Camilla Dalby Hansen · 1×
Citations per year

Countries citing papers authored by Weijing Tang

Since Specialization
Citations

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

Fields of papers citing papers by Weijing Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 2022108
2 202098
3 202120
4 202216
5 202015
6
A Flexible Generative Framework for Graph-based Semi-supervised Learning
201912
7 201612
8 202310
9 20169
10 20189
11 20175
12 20213
13 20243
14 20222
15 20191
16 20201
17
[The change of negative pressure in the cupping-cup and its influence on the depth of filiform-needle insertion].
20101
18 20240
19 20250

About Weijing Tang

Weijing Tang is a scholar working on Epidemiology, Hepatology, Health Information Management, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 19 papers that have together received 325 indexed citations. Recurring topics across this work include Hepatitis C virus research (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Artificial Intelligence in Healthcare (3 papers), Machine Learning in Healthcare (2 papers), Nonlinear Photonic Systems (1 paper), Single-cell and spatial transcriptomics (1 paper), Advanced biosensing and bioanalysis techniques (1 paper) and Alzheimer's disease research and treatments (1 paper). The work is most often cited by research in Hepatology (70 citations), Biological Psychiatry (15 citations), Health Informatics (7 citations), Neurology (42 citations) and Health Information Management (23 citations). Weijing Tang has collaborated with scholars based in United States, China and Iran. Frequent co-authors include Ji Zhu, Monica A. Tincopa, Amit G. Singal, George N. Ioannou, Lauren A. Beste, Elliot B. Tapper, Akbar K. Waljee, Grace L. Su, Tony Van and William E. Lowry. Their work appears in journals such as Journal of the American Statistical Association, Acta Oto-Laryngologica, Radiotherapy and Oncology, Canadian Respiratory Journal and JAMA Network Open.

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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