Yi Liua

5.8k citations
154 papers · 4.5k · 2 hit papers · h-index 31

Impact in

Papers in

Yi Liua

139 papers receiving 4.4k citations

Yi Liua's Hit Papers

Tocilizumab treatment in COVID‐19: A single center experience 2020 · 997 citations
9970+3+6Years since publication250500750

Peers

Yi Liua
Comparison fields: 5 of 153
  • Reproductive Medicine 700
  • Obstetrics and Gynecology 328
  • Infectious Diseases 786
  • Dermatology 375
  • Immunology 774
Replace Ichiro Sekine with:
Ichiro Sekine Japan
Shozo Yoshida Japan
Hua Su China
Fang Li China
Antonio Domenico Procopio Italy
Toshiyuki Kita Japan
Yoshiaki Tanaka Japan
Renu Sarao Canada
Sung‐Chul Lim South Korea
Yi Liua relative to Ichiro Sekine Japan Ichiro Sekine's profile →
Citations per field
00.5×2×4×6.7×
Ichiro Sekine · 1×
Citations per year

Countries citing papers authored by Yi Liua

Since Specialization
Citations

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

Fields of papers citing papers by Yi Liua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 154 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Tocilizumab treatment in COVID‐19: A single center experience
Hit paper breakdown →
2020997
2
Brentuximab vedotin or physician's choice in CD30-positive cutaneous T-cell lymphoma (ALCANZA): an international, open-label, randomised, phase 3, multicentre trial
Hit paper breakdown →
2017450
3 2007302
4 2010139
5 2017115
6 201499
7 201688
8 201788
9 201785
10 201878
11 202077
12 201676
13 201863
14 201861
15 201659
16 202156
17 201954
18 201154
19 201252
20 201551

About Yi Liua

Yi Liua is a scholar working on Reproductive Medicine, Obstetrics and Gynecology, Molecular Biology, Immunology and Cancer Research, having authored 154 papers that have together received 4.5k indexed citations. Recurring topics across this work include Endometriosis Research and Treatment (25 papers), Ovarian function and disorders (11 papers), Reproductive System and Pregnancy (8 papers), Uterine Myomas and Treatments (8 papers), Endometrial and Cervical Cancer Treatments (5 papers), RNA modifications and cancer (5 papers), COVID-19 Clinical Research Studies (5 papers) and Pain Mechanisms and Treatments (5 papers). The work is most often cited by research in Reproductive Medicine (700 citations), Obstetrics and Gynecology (328 citations), Infectious Diseases (786 citations), Dermatology (375 citations) and Immunology (774 citations). Yi Liua has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xiulan Liu, Dong Liu, Lin Qiu, Pan Luo, Juan Li, Wenqian Xiong, Hengwei Liu, Yu Du, Yao Xiong and Wei Gong. Their work appears in journals such as Reproduction, Frontiers in Endocrinology, Biology of Reproduction, The FASEB Journal and Journal of Medical Virology.

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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