Xiang Wan

20.9k citations
133 papers · 14.0k indexed · 3 hit papers · h-index 30

Xiang Wan

124 papers receiving 13.9k citations

Hit Papers

Detecting the skewne...16220142026201820222.5k5.0k7.5k

Peers

Xiang Wan
Comparison fields: 5 of 204
  • Critical Care and Intensive Care Medicine 572
  • Anesthesiology and Pain Medicine 580
  • Surgery 3.4k
  • Cardiology and Cardiovascular Medicine 1.5k
  • Pulmonary and Respiratory Medicine 1.9k
Replace Jiming Liu with:
Jiming Liu Hong Kong
Anna Chaimani France
Caroline J Doré United Kingdom
Georgia Salanti Switzerland
Tiejun Tong Hong Kong
John Concato United States
Nancy A. Obuchowski United States
Atul Malhotra United States
Milo A. Puhan Switzerland
Michał Abrahamowicz Canada
Xiang Wan relative to Jiming Liu Hong Kong Jiming Liu's profile →
Citations per field
00.5×1.5×
Jiming Liu · 1×
Citations per year

Countries citing papers authored by Xiang Wan

Since Specialization
Citations

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

Fields of papers citing papers by Xiang Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20250
4 20243
5 20242
6 20242
7 20244
8 20241
9 20231
10 202364
11 202221
12 20228
13 202148
14 20219
15 202048
16 20153
17
Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile rangebreakdown →
20147836
18 20119
19 200962
20 200340

About Xiang Wan

Xiang Wan is a scholar working on Genetics, Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics and Health Informatics, having authored 133 papers that have together received 14.0k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (24 papers), Topic Modeling (17 papers), Bioinformatics and Genomic Networks (14 papers), Gene expression and cancer classification (12 papers), Natural Language Processing Techniques (11 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers), AI in cancer detection (8 papers) and COVID-19 diagnosis using AI (6 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (572 citations), Anesthesiology and Pain Medicine (580 citations), Surgery (3.4k citations), Cardiology and Cardiovascular Medicine (1.5k citations) and Pulmonary and Respiratory Medicine (1.9k citations). Xiang Wan has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Tiejun Tong, Jiming Liu, Wenqian Wang, Dehui Luo, Can Yang, Weichuan Yu, Yan Song, Qiang Yang, Zhihong Chen and Hong Xue. Their work appears in journals such as Bioinformatics, BMC Bioinformatics, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Medical Imaging and The American Journal of Human Genetics.

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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