Bin Lv

1.1k citations
52 papers · 697 · h-index 15

Impact in

Papers in

Bin Lv

43 papers receiving 692 citations

Peers

Bin Lv
Comparison fields: 5 of 86
  • Internal Medicine 30
  • Cardiology and Cardiovascular Medicine 143
  • Endocrinology, Diabetes and Metabolism 100
  • Critical Care and Intensive Care Medicine 13
  • Surgery 113
Replace Yasuyuki Kawai with:
Yasuyuki Kawai Japan
Frans Beerkens United States
Xing Jin China
C.M. Kirchmaier Germany
J. Musial Poland
Vincenzo Pagliarulo Italy
Hiroki Kinoshita Japan
А. А. Карпов Russia
Joan Minguet Germany
A. Kastrati Germany
Bin Lv relative to Yasuyuki Kawai Japan Yasuyuki Kawai's profile →
Citations per field
00.5×7.5×
Yasuyuki Kawai · 1×
Citations per year

Countries citing papers authored by Bin Lv

Since Specialization
Citations

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

Fields of papers citing papers by Bin Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020105
2 201587
3 201580
4 201942
5 201541
6 202128
7 202223
8 201523
9 201719
10 201217
11 200917
12 201816
13 202014
14 202014
15 201414
16 201713
17 201613
18 201812
19 201911
20 202211

About Bin Lv

Bin Lv is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Molecular Biology, having authored 52 papers that have together received 697 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (9 papers), Thyroid and Parathyroid Surgery (5 papers), Venous Thromboembolism Diagnosis and Management (3 papers), Parathyroid Disorders and Treatments (3 papers), Testicular diseases and treatments (2 papers), Cerebrovascular and Carotid Artery Diseases (2 papers), Cardiac Valve Diseases and Treatments (2 papers) and Lipoproteins and Cardiovascular Health (2 papers). The work is most often cited by research in Internal Medicine (30 citations), Cardiology and Cardiovascular Medicine (143 citations), Endocrinology, Diabetes and Metabolism (100 citations), Critical Care and Intensive Care Medicine (13 citations) and Surgery (113 citations). Bin Lv has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Qingdong Zeng, Luchuan Li, Bo Chen, Han Zhang, Nan Liu, Lili Chen, Lei Sheng, Xiumei Gao, Pan Li and Ting Wang. Their work appears in journals such as Cancer Management and Research, International Journal of Surgery, Surgery, Frontiers in Oncology and Frontiers in Pharmacology.

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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