Lingyu Jiang

26 papers receiving 3.9k citations

Lingyu Jiang's Hit Papers

Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China 2020 · 3.4k citations
3.4k0+2+4Years since publication10002.0k3.0k

Peers

Lingyu Jiang
Comparison fields: 5 of 146
  • Infectious Diseases 2.2k
  • Neurology 1.1k
  • Critical Care and Intensive Care Medicine 115
  • Obstetrics and Gynecology 125
  • Applied Microbiology and Biotechnology 32
Replace Qiurong Ruan with:
Qiurong Ruan China
Vincent W. Li United States
Xiaohu Zheng China
Mohammad Madjid United States
Lingyu Jiang relative to Qiurong Ruan China Qiurong Ruan's profile →
Citations per field
00.5×4.5×
Qiurong Ruan · 1×
Citations per year

Countries citing papers authored by Lingyu Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Lingyu Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China
Hit paper breakdown →
20203440
2 2013136
3 2020102
4 201540
5 200931
6 201528
7 201526
8 202222
9 202222
10 202020
11 201514
12 202013
13 20229
14 20159
15 20167
16 20206
17 20236
18 20205
19 20155
20 20215

About Lingyu Jiang

Lingyu Jiang is a scholar working on Epidemiology, Molecular Biology, Oncology, Biomaterials and Immunology, having authored 26 papers that have together received 4.0k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (3 papers), Nanoparticle-Based Drug Delivery (3 papers), Rabies epidemiology and control (2 papers), Yersinia bacterium, plague, ectoparasites research (2 papers), Immune Cell Function and Interaction (2 papers), Characterization and Applications of Magnetic Nanoparticles (2 papers), Immunotherapy and Immune Responses (2 papers) and Liver Disease and Transplantation (2 papers). The work is most often cited by research in Infectious Diseases (2.2k citations), Neurology (1.1k citations), Critical Care and Intensive Care Medicine (115 citations), Obstetrics and Gynecology (125 citations) and Applied Microbiology and Biotechnology (32 citations). Lingyu Jiang has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Kun Yang, Jianxin Song, Qiurong Ruan, Xiangliang Yang, Huibi Xu, Qing Zhou, Xiao Li, Dufang Ma, Yongcheng Wang and Yanbing Zhao. Their work appears in journals such as Microbial Pathogenesis, Computers in Biology and Medicine, Frontiers in Cellular and Infection Microbiology, BioMed Research International and The Thoracic and Cardiovascular Surgeon.

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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