Lan Lan
Impact in
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- SARS-CoV-2 detection and testing
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- COVID-19 diagnosis using AI 8
- Radiomics and Machine Learning in Medical Imaging 6
- Rheumatology 14
- Systemic Lupus Erythematosus Research 12
- Co-authors
- Haibo Xu (11 shared papers)Dan Xu (8 shared papers)Yirong Li (3 shared papers)Xia Chen (2 shared papers)Shaokang Wang (2 shared papers)Guangming Ye (1 shared paper)Minhua Yu (4 shared papers)Rongguo Zhang (1 shared paper)
- Journals
- Lupus Science & Medicine (4 papers)Frontiers in Cardiovascular Medicine (3 papers)PLoS ONE (3 papers)Molecular and Cellular Endocrinology (2 papers)Journal of Clinical Oncology (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Lan Lan
87 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Infectious Diseases 853
- Modeling and Simulation 103
- Neurology 299
- General Dentistry 34
- Health Informatics 25
Countries citing papers authored by Lan Lan
This map shows the geographic impact of Lan Lan'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 Lan Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan Lan more than expected).
Fields of papers citing papers by Lan Lan
This network shows the impact of papers produced by Lan Lan. 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 Lan Lan. The network helps show where Lan Lan may publish in the future.
Co-authors
The 25 scholars most cited alongside Lan Lan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Positive RT-PCR Test Results in Patients Recovered From COVID-19 Hit paper breakdown → | 2020 | 822 |
| 2 | 2020 | 173 | |
| 3 | 2015 | 113 | |
| 4 | 2020 | 54 | |
| 5 | 2009 | 54 | |
| 6 | 2011 | 52 | |
| 7 | 2020 | 48 | |
| 8 | 2021 | 47 | |
| 9 | 2009 | 42 | |
| 10 | 2020 | 39 | |
| 11 | 2017 | 37 | |
| 12 | 2022 | 33 | |
| 13 | 2012 | 32 | |
| 14 | 2013 | 28 | |
| 15 | 2012 | 27 | |
| 16 | 2020 | 26 | |
| 17 | 2011 | 25 | |
| 18 | 2019 | 23 | |
| 19 | 2016 | 21 | |
| 20 | 2021 | 21 |
About Lan Lan
Lan Lan is a scholar working on Radiology, Nuclear Medicine and Imaging, Rheumatology, Oncology, Pulmonary and Respiratory Medicine and Nephrology, having authored 93 papers that have together received 2.2k indexed citations. Recurring topics across this work include Systemic Lupus Erythematosus Research (12 papers), Renal Diseases and Glomerulopathies (9 papers), COVID-19 diagnosis using AI (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Liver Diseases and Immunity (4 papers), COVID-19 Clinical Research Studies (4 papers), Advanced X-ray and CT Imaging (3 papers) and Cancer, Stress, Anesthesia, and Immune Response (3 papers). The work is most often cited by research in Infectious Diseases (853 citations), Modeling and Simulation (103 citations), Neurology (299 citations), General Dentistry (34 citations) and Health Informatics (25 citations). Lan Lan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Haibo Xu, Dan Xu, Yirong Li, Xia Chen, Shaokang Wang, Guangming Ye, Minhua Yu, Rongguo Zhang, Jianghua Chen and Fei Han. Their work appears in journals such as Lupus Science & Medicine, Frontiers in Cardiovascular Medicine, PLoS ONE, Molecular and Cellular Endocrinology and Journal of Clinical Oncology.
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.