Xiaoying Gu
- Infectious Diseases top 0.02%
- COVID-19 Clinical Research Studies 12
- SARS-CoV-2 and COVID-19 Research 5
- Neurology top 0.05%
- Long-Term Effects of COVID-19 9
- Modeling and Simulation top 0.1%
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- Intensive Care Unit Cognitive Disorders 6
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- Metabolomics and Mass Spectrometry Studies 5
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- Pneumonia and Respiratory Infections 5
- Sepsis Diagnosis and Treatment 4
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- Chronic Obstructive Pulmonary Disease (COPD) Research 4
- Journals
- Clinical Microbiology and Infection (3 papers)The Lancet Respiratory Medicine (2 papers)EBioMedicine (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaoying Gu
42 papers receiving 18.7k citations
Hit Papers
Peers
Comparison fields: 5 of 191
- Infectious Diseases 13.0k
- Neurology 6.8k
- Modeling and Simulation 1.2k
- Critical Care and Intensive Care Medicine 1.3k
- Applied Microbiology and Biotechnology 351
Countries citing papers authored by Xiaoying Gu
This map shows the geographic impact of Xiaoying Gu'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 Xiaoying Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoying Gu more than expected).
Fields of papers citing papers by Xiaoying Gu
This network shows the impact of papers produced by Xiaoying Gu. 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 Xiaoying Gu. The network helps show where Xiaoying Gu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaoying Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 8 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 31 | |
| 8 | 2023 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2022 | 16 | |
| 11 | Health outcomes in people 2 years after surviving hospitalisation with COVID-19: a longitudinal cohort studybreakdown → | 2022 | 354 |
| 12 | 2021 | 10 | |
| 13 | 2021 | 3 | |
| 14 | 2020 | 7 | |
| 15 | 2020 | 6 | |
| 16 | 2020 | 32 | |
| 17 | 2020 | 30 | |
| 18 | 2020 | 9 | |
| 19 | 2019 | 19 | |
| 20 | 2015 | 25 |
About Xiaoying Gu
Xiaoying Gu is a scholar working on Critical Care and Intensive Care Medicine, Acoustics and Ultrasonics, Infectious Diseases, Neurology and Emergency Medicine, having authored 48 papers that have together received 19.2k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (12 papers), Long-Term Effects of COVID-19 (9 papers), Intensive Care Unit Cognitive Disorders (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Pneumonia and Respiratory Infections (5 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (4 papers) and Sepsis Diagnosis and Treatment (4 papers). The work is most often cited by research in Infectious Diseases (13.0k citations), Neurology (6.8k citations), Modeling and Simulation (1.2k citations), Critical Care and Intensive Care Medicine (1.3k citations) and Applied Microbiology and Biotechnology (351 citations). Xiaoying Gu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Bin Cao, Yeming Wang, Guohui Fan, Jiuyang Xu, Fei Zhou, Zhibo Liu, Yi Zhang, Ronghui Du, Xudong Wu and Ting Yu. Their work appears in journals such as Clinical Microbiology and Infection, The Lancet Respiratory Medicine, EBioMedicine, American Journal of Hypertension and Frontiers in Medicine.
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.