Xiaowei Ding

635 citations
16 papers · 234 · h-index 8

Impact in

Papers in

Xiaowei Ding

14 papers receiving 225 citations

Peers

Xiaowei Ding
Comparison fields: 5 of 42
  • Cardiology and Cardiovascular Medicine 110
  • Radiology, Nuclear Medicine and Imaging 96
  • Computer Vision and Pattern Recognition 37
  • Cognitive Neuroscience 32
  • Health Informatics 2
Replace Mohammad Firouzmand with:
Mohammad Firouzmand Iran
Danielle F. Pace United States
Ján Margeta France
Dimitri Kudelski France
Balamurali Murugesan India
Arun Nemani United States
Shahnaz Jamil‐Copley United Kingdom
Tomer Golany Israel
Damian Borys Poland
Yanping Xue China
Xiaowei Ding relative to Mohammad Firouzmand Iran Mohammad Firouzmand's profile →
Citations per field
00.5×1.5×1.9×
Mohammad Firouzmand · 1×
Citations per year

Countries citing papers authored by Xiaowei Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xiaowei Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 201647
2 201941
3 201535
4 201332
5 201422
6 201921
7 201510
8 20209
9 20167
10 20223
11
Automated Pericardial Fat Quantification from Coronary Magnetic Resonance Angiography.
20153
12 20242
13 20241
14
Automated Quantitative Analysis of Cardiac Medical Images
20151
15 20230
16 20250

About Xiaowei Ding

Xiaowei Ding is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Artificial Intelligence and Ophthalmology, having authored 16 papers that have together received 234 indexed citations. Recurring topics across this work include Cardiovascular Disease and Adiposity (6 papers), Cardiac Imaging and Diagnostics (5 papers), Retinal Imaging and Analysis (4 papers), Cardiovascular Function and Risk Factors (4 papers), Digital Imaging for Blood Diseases (2 papers), Retinal and Optic Conditions (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (110 citations), Radiology, Nuclear Medicine and Imaging (96 citations), Computer Vision and Pattern Recognition (37 citations), Cognitive Neuroscience (32 citations) and Health Informatics (2 citations). Xiaowei Ding has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Demetri Terzopoulos, Damini Dey, Daniel S. Berman, Piotr J. Slomka, Mariana Díaz‐Zamudio, Nima Tajbakhsh, Junying Liang, Zaifeng Gao, Rende Shui and Jianming Liang. Their work appears in journals such as Medical Physics, Psychological Research, IEEE Journal of Biomedical and Health Informatics, Journal of cardiovascular computed tomography and PLoS ONE.

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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