Ge Shi

415 citations
15 papers · 320 · 1 hit paper · h-index 6

Impact in

Papers in

Ge Shi

14 papers receiving 320 citations

Ge Shi's Hit Papers

Bioinspired wet adhesive carboxymethyl cellulose-based hydrogel with rapid shape adaptability and antioxidant activity for diabetic wound repair 2024 · 55 citations
550+1Years since publication1020304050

Peers

Ge Shi
Comparison fields: 5 of 60
  • Rehabilitation 37
  • Oncology 87
  • Molecular Medicine 16
  • Biomaterials 35
  • Pulmonary and Respiratory Medicine 70
Replace Dakota J. Suchyta with:
Dakota J. Suchyta United States
Sooseok Im South Korea
Ju‐E Cun China
Qiong Yuan China
Yingtao Zhong China
Linqian Hou China
Xiance Wang China
Chenqi Guo China
Weifei Lu China
Ge Shi relative to Dakota J. Suchyta United States Dakota J. Suchyta's profile →
Citations per field
00.5×
Dakota J. Suchyta · 1×
Citations per year

Countries citing papers authored by Ge Shi

Since Specialization
Citations

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

Fields of papers citing papers by Ge Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 201494
2 201490
3
Bioinspired wet adhesive carboxymethyl cellulose-based hydrogel with rapid shape adaptability and antioxidant activity for diabetic wound repair
Hit paper breakdown →
202455
4 202132
5 202124
6 20239
7 20234
8 20244
9 20162
10 20192
11 20251
12 20251
13 20241
14 20191
15 20240

About Ge Shi

Ge Shi is a scholar working on Surgery, Pulmonary and Respiratory Medicine, Oncology, Computer Vision and Pattern Recognition and Ophthalmology, having authored 15 papers that have together received 320 indexed citations. Recurring topics across this work include Surgical Simulation and Training (2 papers), Photodynamic Therapy Research Studies (2 papers), Surgical Sutures and Adhesives (2 papers), Glaucoma and retinal disorders (2 papers), Retinal Diseases and Treatments (2 papers), Metal complexes synthesis and properties (2 papers), Augmented Reality Applications (2 papers) and Click Chemistry and Applications (1 paper). The work is most often cited by research in Rehabilitation (37 citations), Oncology (87 citations), Molecular Medicine (16 citations), Biomaterials (35 citations) and Pulmonary and Respiratory Medicine (70 citations). Ge Shi has collaborated with scholars based in Canada, China and Japan. Frequent co-authors include Tariq Sainuddin, Sherri A. McFarland, H. Yin, Susan Monro, Eric J. Sampson, Qianqian Chen, Ruizi Wang, Aixi Yu, Ang Lu and Hongxia Xie. Their work appears in journals such as Experimental Eye Research, Journal of Orthopaedic Surgery and Research, Carbohydrate Polymers, PLoS ONE and Dermatologic Surgery.

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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