Kai‐Ni Wang

537 citations
18 papers · 333 · h-index 9

Impact in

Papers in

Kai‐Ni Wang

16 papers receiving 327 citations

Peers

Kai‐Ni Wang
Comparison fields: 5 of 77
  • Transportation 83
  • General Economics, Econometrics and Finance 76
  • Computer Vision and Pattern Recognition 68
  • Neurology 22
  • Radiology, Nuclear Medicine and Imaging 56
Replace Dario García-Gasulla with:
Dario García-Gasulla Spain
Mohammad Mehdi Movahedi Iran
Bjorn Thomas United Kingdom
Zhicheng Liang China
Chunan Wang China
Alan Kwan Hong Kong
Irfan Ali Pakistan
Tri Widodo Indonesia
Dongqing Zhu China
Pavel Čech Czechia
Kai‐Ni Wang relative to Dario García-Gasulla Spain Dario García-Gasulla's profile →
Citations per field
00.5×10×12.7×
Dario García-Gasulla · 1×
Citations per year

Countries citing papers authored by Kai‐Ni Wang

Since Specialization
Citations

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

Fields of papers citing papers by Kai‐Ni Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2018133
2 202242
3 201325
4 202324
5 202420
6 202317
7 202315
8 202015
9 202413
10 20236
11 20235
12 20185
13 20234
14 20234
15 20234
16 20251
17 20240
18 20240

About Kai‐Ni Wang

Kai‐Ni Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Surgery and Oncology, having authored 18 papers that have together received 333 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), AI in cancer detection (4 papers), Colorectal Cancer Screening and Detection (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Orthopedic Surgery and Rehabilitation (2 papers), Aviation Industry Analysis and Trends (2 papers), Transportation Planning and Optimization (2 papers) and Image Retrieval and Classification Techniques (2 papers). The work is most often cited by research in Transportation (83 citations), General Economics, Econometrics and Finance (76 citations), Computer Vision and Pattern Recognition (68 citations), Neurology (22 citations) and Radiology, Nuclear Medicine and Imaging (56 citations). Kai‐Ni Wang has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Wei Su, Yanyan Gao, Guangquan Zhou, Yang Chen, Ping Zhou, Juzheng Miao, Chi Zhang, Min Ji, Yong‐Lin An and Wufeng Xue. Their work appears in journals such as Medical Image Analysis, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Tourism Management 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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