Fengxia Shi

1.4k citations
16 papers · 1.0k · 1 hit paper · h-index 11

Impact in

    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research
  • Oncology top 5%
    • CAR-T cell therapy research

Papers in

Fengxia Shi

16 papers receiving 981 citations

Fengxia Shi's Hit Papers

C‐reactive protein correlates with computed tomographic findings and predicts severe COVID‐19 early 2020 · 392 citations
3920+2+4Years since publication100200300

Peers

Fengxia Shi
Comparison fields: 5 of 80
  • Infectious Diseases 379
  • Oncology 517
  • Neurology 219
  • Immunology 153
  • Critical Care and Intensive Care Medicine 23
Replace Alexandre V. Hirayama with:
Alexandre V. Hirayama United States
Robert Q. Le United States
Anders Tveita Norway
Pak K. Hui China
Kong Ling Mak China
Mehran Habibi United States
Chung Ying Leung China
Tommaso Lorenzo Parigi Italy
Changcheng Zheng China
Christina Price United States
Fengxia Shi relative to Alexandre V. Hirayama United States Alexandre V. Hirayama's profile →
Citations per field
00.5×12.3×
Alexandre V. Hirayama · 1×
Citations per year

Countries citing papers authored by Fengxia Shi

Since Specialization
Citations

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

Fields of papers citing papers by Fengxia Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1
C‐reactive protein correlates with computed tomographic findings and predicts severe COVID‐19 early
Hit paper breakdown →
2020392
2 2015134
3 2020125
4 2016104
5 201450
6 202148
7 202046
8 202129
9 201829
10 201916
11 201614
12 20149
13 20185
14 20212
15 20211
16 20211

About Fengxia Shi

Fengxia Shi is a scholar working on Oncology, Pathology and Forensic Medicine, Immunology, Surgery and Infectious Diseases, having authored 16 papers that have together received 1.0k indexed citations. Recurring topics across this work include CAR-T cell therapy research (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Immune Cell Function and Interaction (4 papers), Long-Term Effects of COVID-19 (2 papers), Pancreatitis Pathology and Treatment (2 papers), Viral-associated cancers and disorders (2 papers), COVID-19 Clinical Research Studies (2 papers) and Sepsis Diagnosis and Treatment (2 papers). The work is most often cited by research in Infectious Diseases (379 citations), Oncology (517 citations), Neurology (219 citations), Immunology (153 citations) and Critical Care and Intensive Care Medicine (23 citations). Fengxia Shi has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Chaochao Tan, Ying Huang, Yong Chen, Kui Tan, Xixin Jiang, Xiaosong Li, Weidong Han, Yao Wang, Kaichao Feng and Yelei Guo. Their work appears in journals such as Cytotherapy, Clinical Cancer Research, Korean Journal of Radiology, Journal of Medical Virology and Science China Life Sciences.

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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