Weibo Mao

502 citations
22 papers · 316 · 1 hit paper · h-index 10

Impact in

Papers in

Weibo Mao

20 papers receiving 311 citations

Weibo Mao's Hit Papers

Leapfrog Diffusion Model for Stochastic Trajectory Prediction 2023 · 113 citations
1130+1+2Years since publication255075100

Peers

Weibo Mao
Comparison fields: 5 of 71
  • Gastroenterology 31
  • Automotive Engineering 77
  • Safety, Risk, Reliability and Quality 33
  • Building and Construction 44
  • Computer Vision and Pattern Recognition 50
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Shuang Wen China
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Yinghao Zhang China
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Countries citing papers authored by Weibo Mao

Since Specialization
Citations

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

Fields of papers citing papers by Weibo Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Leapfrog Diffusion Model for Stochastic Trajectory Prediction
Hit paper breakdown →
2023113
2 201428
3 202025
4 202024
5
[Epidemiological survey of chronic vascular complications of type 2 diabetic in-patients in four municipalities].
200219
6 201614
7 201714
8 202113
9 201711
10 20159
11 20248
12 20197
13 20257
14 20057
15 20244
16 20244
17 20253
18 20183
19 20242
20 20171

About Weibo Mao

Weibo Mao is a scholar working on Radiology, Nuclear Medicine and Imaging, Automotive Engineering, Neurology, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 22 papers that have together received 316 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Advanced X-ray and CT Imaging (2 papers), Autonomous Vehicle Technology and Safety (2 papers), Endometrial and Cervical Cancer Treatments (2 papers), Gastrointestinal Tumor Research and Treatment (2 papers), Sarcoma Diagnosis and Treatment (1 paper), Endometriosis Research and Treatment (1 paper) and Transportation and Mobility Innovations (1 paper). The work is most often cited by research in Gastroenterology (31 citations), Automotive Engineering (77 citations), Safety, Risk, Reliability and Quality (33 citations), Building and Construction (44 citations) and Computer Vision and Pattern Recognition (50 citations). Weibo Mao has collaborated with scholars based in China, Germany and South Korea. Frequent co-authors include Chenxin Xu, Qi Zhu, Siheng Chen, Yanfeng Wang, Chenying Lu, Jiansong Ji, Min Xu, Qiaoyou Weng, Xuemei Mao and Wei Zheng. Their work appears in journals such as Medicine, PeerJ, Frontiers in Oncology, Academic Radiology and Oncotarget.

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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