Xi Ouyang

72 papers receiving 2.4k citations

Xi Ouyang's Hit Papers

A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory 2017 · 401 citations
4010+3+6Years since publication100200300400

Peers

Xi Ouyang
Comparison fields: 5 of 168
  • Health Informatics 103
  • Radiological and Ultrasound Technology 277
  • Radiology, Nuclear Medicine and Imaging 440
  • Artificial Intelligence 678
  • Computer Vision and Pattern Recognition 355
Replace Vitoantonio Bevilacqua with:
Vitoantonio Bevilacqua Italy
Mohammed Hossny Australia
Xuewei Li China
Yu Cao United States
Marcin Grzegorzek Germany
Syed Saad Azhar Ali Malaysia
Tamer Abuhmed South Korea
Malika Bendechache Ireland
Lei Qi China
Jun Xiao China
Xi Ouyang relative to Vitoantonio Bevilacqua Italy Vitoantonio Bevilacqua's profile →
Citations per field
00.5×8.1×
Vitoantonio Bevilacqua · 1×
Citations per year

Countries citing papers authored by Xi Ouyang

Since Specialization
Citations

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

Fields of papers citing papers by Xi Ouyang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory
Hit paper breakdown →
2017401
2 2020287
3 2015172
4 2018168
5 2006112
6 2011110
7 202095
8 201885
9 200885
10 202471
11 201764
12 202061
13 200959
14 201957
15 201955
16 201752
17 201830
18 202228
19 202128
20 202223

About Xi Ouyang

Xi Ouyang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 74 papers that have together received 2.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (11 papers), COVID-19 diagnosis using AI (6 papers), Medical Image Segmentation Techniques (4 papers), Sexual function and dysfunction studies (4 papers), Lung Cancer Diagnosis and Treatment (4 papers), Artificial Intelligence in Healthcare and Education (4 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Health Informatics (103 citations), Radiological and Ultrasound Technology (277 citations), Radiology, Nuclear Medicine and Imaging (440 citations), Artificial Intelligence (678 citations) and Computer Vision and Pattern Recognition (355 citations). Xi Ouyang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Peter E.D. Love, Hanbin Luo, Weili Fang, Lieyun Ding, Botao Zhong, Pan Zhou, Qian Wang, Dinggang Shen, Lijun Liu and Junxia Chen. Their work appears in journals such as IEEE Transactions on Medical Imaging, Journal of Material Science and Technology, Lupus, Neuroscience and Automation in Construction.

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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