Luoting Zhuang

612 citations
5 papers · 336 indexed · 1 hit paper · h-index 2
Topics
Radiomics and Machine Learning in Medical Imaging (5 papers)AI in cancer detection (3 papers)Lung Cancer Diagnosis and Treatment (2 papers)
Partner nations
United States

In The Last Decade

Luoting Zhuang

3 papers receiving 332 citations

Hit Papers

Artificial intelligence for multimodal data integration i...20222026202320242022100200300

Peers

Luoting Zhuang
Comparison fields: 5 of 75
  • Radiology, Nuclear Medicine and Imaging 170
  • Artificial Intelligence 157
  • Health Informatics 69
  • Molecular Biology 55
  • Cancer Research 52
Replace Peter Truszkowski with:
Peter Truszkowski United States
Ivy Liang United States
Charles Maussion France
Manuela Vecsler United States
Ann-Christin Woerl Germany
Maha Shady United States
Arash Mohtashamian United States
Christina Glasner Germany
Andrew Zhang United States
Aurélie Fernandez Germany
Luoting Zhuang relative to Peter Truszkowski United States Peter Truszkowski's profile →
Citations per field
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Peter Truszkowski · 1×
Citations per year

Countries citing papers authored by Luoting Zhuang

Since Specialization
Citations

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

Fields of papers citing papers by Luoting Zhuang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luoting Zhuang

This figure shows the co-authorship network connecting the top 25 collaborators of Luoting Zhuang. A scholar is included among the top collaborators of Luoting Zhuang 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 Luoting Zhuang. Luoting Zhuang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
#WorkIndexed citations
1 0
2 0
3
Patient-level thyroid cancer classification using attention multiple instance learning on fused multi-scale ultrasound image features.
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Artificial intelligence for multimodal data integration in oncologybreakdown →
333
5 2

About Luoting Zhuang

Luoting Zhuang is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 5 papers that have together received 336 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (3 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (69 citations), Radiology, Nuclear Medicine and Imaging (170 citations) and Artificial Intelligence (157 citations). Luoting Zhuang has collaborated with scholars based in United States. Frequent co-authors include Muhammad Shaban, Faisal Mahmood, Bowen Chen, Anurag Vaidya, Tiffany Chen, Chengkuan Chen, Jana Lipková, Ming Y. Lu, Richard J. Chen and Drew F. K. Williamson. Their work appears in journals such as Cancer Cell, IEEE Reviews in Biomedical Engineering and PubMed.

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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