He Sui

811 citations
18 papers · 511 · h-index 8

Impact in

Papers in

    • Anomaly Detection Techniques and Applications 6
    • Imbalanced Data Classification Techniques 2
    • AI in cancer detection 2
    • COVID-19 diagnosis using AI 3
    • Radiomics and Machine Learning in Medical Imaging 3
    • Advanced MRI Techniques and Applications 2
    • Ultrasound Imaging and Elastography 1

He Sui

15 papers receiving 494 citations

Peers

He Sui
Comparison fields: 5 of 81
  • Health Informatics 69
  • Radiology, Nuclear Medicine and Imaging 312
  • Artificial Intelligence 238
  • Neurology 45
  • Health Information Management 20
Replace Neha Gianchandani with:
Neha Gianchandani Canada
Huan Yuan China
Vaibhav Arora India
Junaid Latief Shah India
Bejoy Abraham India
Mohammed Meknassi Morocco
Rodolfo M. Pereira Brazil
Deepti Mittal India
Juan Luis Suárez Spain
Tej Bahadur Chandra India
He Sui relative to Neha Gianchandani Canada Neha Gianchandani's profile →
Citations per field
00.5×1.5×1.8×
Neha Gianchandani · 1×
Citations per year

Countries citing papers authored by He Sui

Since Specialization
Citations

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

Fields of papers citing papers by He Sui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2020176
2 2020170
3 202056
4 202047
5 202313
6 202410
7 20247
8 20237
9 20225
10 20235
11 20244
12
Accelerating Knee MRI: 3D Modulated Flip-Angle Technique in Refocused Imaging with an Extended Echo Train and Compressed Sensing
20224
13 20253
14 20232
15 20252
16 20240
17 20250
18 20240

About He Sui

He Sui is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications, Computer Vision and Pattern Recognition and Epidemiology, having authored 18 papers that have together received 511 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (6 papers), Network Security and Intrusion Detection (4 papers), COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Imbalanced Data Classification Techniques (2 papers), Advanced MRI Techniques and Applications (2 papers), AI in cancer detection (2 papers) and Ultrasound Imaging and Elastography (1 paper). The work is most often cited by research in Health Informatics (69 citations), Radiology, Nuclear Medicine and Imaging (312 citations), Artificial Intelligence (238 citations), Neurology (45 citations) and Health Information Management (20 citations). He Sui has collaborated with scholars based in China and South Korea. Frequent co-authors include Feng Shi, Dinggang Shen, Liming Xia, Dijia Wu, Huan Yuan, Zhanhao Mo, Yaozong Gao, Changqing Zhang, Fuhua Yan and Fei Shan. Their work appears in journals such as Scientific Reports, Frontiers in Endocrinology, Journal of Pain Research, Medical Image Analysis and PLoS ONE.

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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