Xuming Dai

1.8k citations
54 papers · 1.1k · h-index 19

Impact in

Papers in

Xuming Dai

49 papers receiving 1.1k citations

Peers

Xuming Dai
Comparison fields: 5 of 109
  • Internal Medicine 53
  • Cardiology and Cardiovascular Medicine 339
  • Radiology, Nuclear Medicine and Imaging 141
  • Neurology 41
  • Geriatrics and Gerontology 15
Replace Pankaj Saxena with:
Pankaj Saxena Australia
Ralf Kaiser Germany
Philipp Diehl Germany
Claire Bouleti France
Peter Stachon Germany
Zhiwei Zhang China
Moussa Mansour United States
Deepak M. Gangahar United States
Michael Fritzenwanger Germany
Kan Zen Japan
Xuming Dai relative to Pankaj Saxena Australia Pankaj Saxena's profile →
Citations per field
00.5×3.8×
Pankaj Saxena · 1×
Citations per year

Countries citing papers authored by Xuming Dai

Since Specialization
Citations

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

Fields of papers citing papers by Xuming Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016147
2 2010115
3 202184
4 201779
5 201073
6 201770
7 201653
8 201440
9 202139
10 202039
11 201539
12 201336
13 201735
14 201825
15 201625
16 201523
17 201621
18 201720
19 201820
20 202113

About Xuming Dai

Xuming Dai is a scholar working on Cardiology and Cardiovascular Medicine, Surgery, Radiology, Nuclear Medicine and Imaging, Internal Medicine and Immunology, having authored 54 papers that have together received 1.1k indexed citations. Recurring topics across this work include Acute Myocardial Infarction Research (16 papers), Cardiac Imaging and Diagnostics (6 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Cardiac, Anesthesia and Surgical Outcomes (5 papers), Ultrasound and Hyperthermia Applications (4 papers), Heart Failure Treatment and Management (4 papers), Photoacoustic and Ultrasonic Imaging (3 papers) and Coronary Interventions and Diagnostics (2 papers). The work is most often cited by research in Internal Medicine (53 citations), Cardiology and Cardiovascular Medicine (339 citations), Radiology, Nuclear Medicine and Imaging (141 citations), Neurology (41 citations) and Geriatrics and Gerontology (15 citations). Xuming Dai has collaborated with scholars based in United States, Hong Kong and China. Frequent co-authors include James E. Faber, Karen P. Alexander, Xiaoning Jiang, George A. Stouffer, Sidney C. Smith, Jan Busby‐Whitehead, Chang Peng, Seungsoo Kim, Huaiyu Wu and Shiliang Wang. Their work appears in journals such as Journal of the American College of Cardiology, The FASEB Journal, ˜The œJournal of invasive cardiology, Catheterization and Cardiovascular Interventions and Circulation 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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