Haichen Lv

605 citations
36 papers · 376 indexed · h-index 12

Impact in

Papers in

Haichen Lv

32 papers receiving 371 citations

Peers

Haichen Lv
Comparison fields: 5 of 83
  • Cardiology and Cardiovascular Medicine 172
  • Internal Medicine 21
  • Obstetrics and Gynecology 34
  • Surgery 116
  • Radiology, Nuclear Medicine and Imaging 60
Replace Gabriele Cioni with:
Gabriele Cioni Italy
Akif Arslan Türkiye
Jiajun Zhu China
Daniela Zanetti United States
Karen Kato Japan
Oddgeir L. Holmen Norway
Brodie Loudon United Kingdom
Ta‐Chuan Hung Taiwan
Malik Elharram Canada
Maria Hughes United Kingdom
Haichen Lv relative to Gabriele Cioni Italy Gabriele Cioni's profile →
Citations per field
00.5×4.7×
Gabriele Cioni · 1×
Citations per year

Countries citing papers authored by Haichen Lv

Since Specialization
Citations

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

Fields of papers citing papers by Haichen Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201549
2 202036
3 201626
4 202022
5 202020
6 201720
7 202117
8 201317
9 201917
10 202216
11 202016
12 201611
13 202111
14 20219
15 20198
16 20218
17 20208
18 20238
19 20227
20 20237

About Haichen Lv

Haichen Lv is a scholar working on Cardiology and Cardiovascular Medicine, Surgery, Radiology, Nuclear Medicine and Imaging, Internal Medicine and Oncology, having authored 36 papers that have together received 376 indexed citations. Recurring topics across this work include Coronary Interventions and Diagnostics (14 papers), Cardiac Imaging and Diagnostics (10 papers), Acute Myocardial Infarction Research (9 papers), Antiplatelet Therapy and Cardiovascular Diseases (7 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Cardiovascular Issues in Pregnancy (4 papers), Inflammatory Biomarkers in Disease Prognosis (3 papers) and Gout, Hyperuricemia, Uric Acid (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (172 citations), Internal Medicine (21 citations), Obstetrics and Gynecology (34 citations), Surgery (116 citations) and Radiology, Nuclear Medicine and Imaging (60 citations). Haichen Lv has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Lei Guo, Rongchong Huang, Hongyi Wu, Juying Qian, Junbo Ge, Xiaolei Yang, Huaiyu Ding, Lei Zhong, Jiaying Xu and Yunlong Xia. Their work appears in journals such as Scientific Reports, Frontiers in Cardiovascular Medicine, Clinical Interventions in Aging, Cardiovascular Diabetology and Journal of Inflammation Research.

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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