Kai Gao

772 citations
40 papers · 530 · h-index 12

Impact in

Papers in

Kai Gao

37 papers receiving 516 citations

Peers

Kai Gao
Comparison fields: 5 of 112
  • Health Informatics 37
  • Radiology, Nuclear Medicine and Imaging 145
  • Artificial Intelligence 144
  • Infectious Diseases 60
  • Neurology 27
Replace Yuanfang Chen with:
Yuanfang Chen China
Md. Rashed-Al-Mahfuz Bangladesh
Sujit Kumar Das India
Jianing Qiu United Kingdom
Maí­ra Araújo de Santana Brazil
Xianghao Zhan United States
Shayan Hassantabar United States
Ghada Zamzmi United States
Abhishek Gupta India
Kai Gao relative to Yuanfang Chen China Yuanfang Chen's profile →
Citations per field
00.5×1.5×2.3×
Yuanfang Chen · 1×
Citations per year

Countries citing papers authored by Kai Gao

Since Specialization
Citations

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

Fields of papers citing papers by Kai Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kai Gao, 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 Gao Line = papers co-authored together Kai Gao 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 2020143
2 201639
3 201438
4 202334
5 202033
6 201433
7 202327
8 200224
9 201619
10 202214
11 202013
12 202013
13 202111
14 202111
15 201810
16 20199
17 20138
18 20246
19
[Characteristics and changes of landscape pattern in Wuhan City based on Ripley's K function].
20105
20 20204

About Kai Gao

Kai Gao is a scholar working on Artificial Intelligence, Computer Networks and Communications, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Information Systems, having authored 40 papers that have together received 530 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (5 papers), Topic Modeling (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Remote Sensing and Land Use (2 papers), Anomaly Detection Techniques and Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Advanced Neuroimaging Techniques and Applications (2 papers) and Target Tracking and Data Fusion in Sensor Networks (2 papers). The work is most often cited by research in Health Informatics (37 citations), Radiology, Nuclear Medicine and Imaging (145 citations), Artificial Intelligence (144 citations), Infectious Diseases (60 citations) and Neurology (27 citations). Kai Gao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Dewen Hu, Ling‐Li Zeng, Yanping Song, Jianpo Su, Hui Shen, Zhichao Feng, Wei Wang, Pengfei Rong, Jian Qin and Xin Xu. Their work appears in journals such as Medicine, Biological Psychiatry, Frontiers in Earth Science, Clinical and Translational Medicine and BMC Infectious Diseases.

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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