Zhaoshuo Diao

456 citations
15 papers · 279 indexed · 1 hit paper · h-index 7
Topics
Radiomics and Machine Learning in Medical Imaging (12 papers)Medical Imaging Techniques and Applications (6 papers)Advanced X-ray and CT Imaging (5 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Zhaoshuo Diao

13 papers receiving 269 citations

Hit Papers

A review of deep learning-based multiple-lesion recogniti...202320262024202520234080120

Peers

Zhaoshuo Diao
Comparison fields: 5 of 83
  • Radiology, Nuclear Medicine and Imaging 135
  • Computer Vision and Pattern Recognition 97
  • Artificial Intelligence 95
  • Neurology 62
  • Pulmonary and Respiratory Medicine 35
Replace Rushi Jiao with:
Rushi Jiao China
Abin Jose Germany
Lisa Di Jorio Canada
Yassir Edrees Almalki Saudi Arabia
Nor Aniza Azmi Malaysia
Grzegorz Chlebus Germany
Xuanya Li China
Yinghao Zhang China
Yeşim Eroğlu Türkiye
Subrata Bhattacharjee South Korea
Zhaoshuo Diao relative to Rushi Jiao China Rushi Jiao's profile →
Citations per field
00.5×3.5×
Rushi Jiao · 1×
Citations per year

Countries citing papers authored by Zhaoshuo Diao

Since Specialization
Citations

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

Fields of papers citing papers by Zhaoshuo Diao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaoshuo Diao

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 0
2 11
3 6
4 4
5 5
6 0
7
A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentationbreakdown →
135
8 9
9 3
10 8
11 5
12 17
13 2
14 23
15 51

About Zhaoshuo Diao

Zhaoshuo Diao is a scholar working on Radiology, Nuclear Medicine and Imaging, Otorhinolaryngology and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 279 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (6 papers) and Advanced X-ray and CT Imaging (5 papers). The work is most often cited by research in Neurology (62 citations), Health Informatics (10 citations) and Radiology, Nuclear Medicine and Imaging (135 citations). Zhaoshuo Diao has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Huiyan Jiang, Yudong Yao, Tianyu Shi, Xiaolin Zhu, Yang Zhou, Feiyu Wang, Xian‐Hua Han, Yang Zhou, Yaming Li and Weijing Zhang. Their work appears in journals such as Expert Systems with Applications, Physics in Medicine and Biology and Knowledge-Based Systems.

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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