Xuanyu Wu

701 citations
27 papers · 375 indexed · 1 hit paper · h-index 9
Topics
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (7 papers)Occupational and environmental lung diseases (3 papers)Neural dynamics and brain function (3 papers)

In The Last Decade

Xuanyu Wu

18 papers receiving 369 citations

Hit Papers

Interpretable deep learning: interpretation, interpretabi...2022202620232024202250100150200

Peers

Xuanyu Wu
Comparison fields: 5 of 129
  • Artificial Intelligence 114
  • Molecular Biology 48
  • Computer Vision and Pattern Recognition 41
  • Electrical and Electronic Engineering 40
  • Pulmonary and Respiratory Medicine 33
Replace Moolchand Sharma with:
Moolchand Sharma India
Amani K. Samha Saudi Arabia
Jinyong Cheng China
S. T. Patil India
Mohammad Abdul Azim Bangladesh
Hui Yu China
Daniel Harborne United Kingdom
Francisco J. Moreno-Barea Spain
Esraa Hassan Egypt
Zulfikar Alom Bangladesh
Xuanyu Wu relative to Moolchand Sharma India Moolchand Sharma's profile →
Citations per field
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Moolchand Sharma · 1×
Citations per year

Countries citing papers authored by Xuanyu Wu

Since Specialization
Citations

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

Fields of papers citing papers by Xuanyu Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuanyu Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Xuanyu Wu. A scholar is included among the top collaborators of Xuanyu Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xuanyu Wu. Xuanyu Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyondbreakdown →
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About Xuanyu Wu

Xuanyu Wu is a scholar working on Developmental Biology, Geriatrics and Gerontology and Pulmonary and Respiratory Medicine, having authored 27 papers that have together received 375 indexed citations. Recurring topics across this work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (7 papers), Occupational and environmental lung diseases (3 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (114 citations) and Computer Vision and Pattern Recognition (41 citations). Xuanyu Wu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Dejing Dou, Ji Liu, Jiang Bian, Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Yixiong Feng, Zhaoxi Hong and Shanhe Lou. Their work appears in journals such as PLoS ONE, Scientific Reports and Frontiers in Immunology.

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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