Lanbo Yang

10 papers receiving 593 citations

Lanbo Yang's Hit Papers

Predictors of COVID‐19 severity: A literature review 2020 · 542 citations
5420+2+4Years since publication100200300400500

Peers

Lanbo Yang
Comparison fields: 5 of 108
  • Infectious Diseases 360
  • Neurology 170
  • Modeling and Simulation 36
  • Critical Care and Intensive Care Medicine 35
  • Health Informatics 6
Replace Martín Ragusa with:
Martín Ragusa Argentina
Fernando Tortosa Argentina
Jun Heng Chong United Kingdom
A Bengolea Argentina
Verónica Sanguine Argentina
Camila Agnoletti Argentina
Ezequiel Saavedra Argentina
Federico Espinosa Argentina
Benjamin Gallo Marin United States
Qianling Shi China
Lanbo Yang relative to Martín Ragusa Argentina Martín Ragusa's profile →
Citations per field
00.5×1.5×
Martín Ragusa · 1×
Citations per year

Countries citing papers authored by Lanbo Yang

Since Specialization
Citations

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

Fields of papers citing papers by Lanbo Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Predictors of COVID‐19 severity: A literature review
Hit paper breakdown →
2020542
2 201918
3 201716
4 20228
5 20235
6 20205
7 20162
8 20231
9 20251
10 20241
11 20240
12 20240

About Lanbo Yang

Lanbo Yang is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Physiology, Molecular Biology and Cellular and Molecular Neuroscience, having authored 12 papers that have together received 599 indexed citations. Recurring topics across this work include HIV/AIDS Research and Interventions (5 papers), Syphilis Diagnosis and Treatment (3 papers), HIV, Drug Use, Sexual Risk (2 papers), Reproductive tract infections research (2 papers), Photoreceptor and optogenetics research (2 papers), Retinal Development and Disorders (2 papers), Retinal Diseases and Treatments (1 paper) and HIV Research and Treatment (1 paper). The work is most often cited by research in Infectious Diseases (360 citations), Neurology (170 citations), Modeling and Simulation (36 citations), Critical Care and Intensive Care Medicine (35 citations) and Health Informatics (6 citations). Lanbo Yang has collaborated with scholars based in United States, Peru and Brazil. Frequent co-authors include Benjamin Gallo Marin, Ghazal Aghagoli, Silvia S. Chiang, Timothy Flanigan, Luba Dumenco, Su Aung, Thais P. Salazar‐Mather, Ian C. Michelow, Karin Nielsen‐Saines and Kin‐Sang Cho. Their work appears in journals such as Current HIV/AIDS Reports, Human Gene Therapy, Reviews in Medical Virology, Sexually Transmitted Diseases and Injury.

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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