Rushuang Mao

799 citations
12 papers · 521 indexed · 1 hit paper · h-index 7
Topics
Radiomics and Machine Learning in Medical Imaging (7 papers)AI in cancer detection (5 papers)Hepatocellular Carcinoma Treatment and Prognosis (4 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaFrontiers in Oncology
Partner nations
China

In The Last Decade

Rushuang Mao

11 papers receiving 515 citations

Hit Papers

Deep learning radiomics can predict axillary lymph node s...20202026202220242020100200300400

Peers

Rushuang Mao
Comparison fields: 5 of 60
  • Radiology, Nuclear Medicine and Imaging 415
  • Artificial Intelligence 237
  • Biomedical Engineering 93
  • Pulmonary and Respiratory Medicine 85
  • Cancer Research 82
Replace Yixin Hu with:
Yixin Hu China
Yini Huang China
Xueyi Zheng China
Renée W. Y. Granzier Netherlands
Jianqiao Zhou China
Ko Woon Park South Korea
Manon Beuque Netherlands
Christina Dubchuk United States
Mireia Crispin‐Ortuzar United Kingdom
Camilla Scapicchio Italy
Rushuang Mao relative to Yixin Hu China Yixin Hu's profile →
Citations per field
00.5×1.5×
Yixin Hu · 1×
Citations per year

Countries citing papers authored by Rushuang Mao

Since Specialization
Citations

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

Fields of papers citing papers by Rushuang Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rushuang Mao

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 1
2 0
3 3
4 39
5 2
6 14
7 13
8 12
9 8
10
Deep learning radiomics can predict axillary lymph node status in early-stage breast cancerbreakdown →
402
11 5
12 22

About Rushuang Mao

Rushuang Mao is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 12 papers that have together received 521 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (5 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Health Informatics (28 citations), Radiology, Nuclear Medicine and Imaging (415 citations) and Artificial Intelligence (237 citations). Rushuang Mao has collaborated with scholars based in China. Frequent co-authors include Jianhua Zhou, Yun Wang, Yini Huang, Yixin Hu, Fei Li, Xueyi Zheng, Yubo Liu, Yuanyuan Wang, Yao Zhao and Jinhua Yu. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Frontiers in Oncology.

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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