Can Liu

31 papers receiving 399 citations

Peers

Can Liu
Comparison fields: 5 of 91
  • Obstetrics and Gynecology 38
  • Clinical Psychology 92
  • Pediatrics, Perinatology and Child Health 65
  • Neurology 28
  • Safety Research 27
Replace Margaret Carroll with:
Margaret Carroll Ireland
Kam Sripada Norway
Katrina M. Moss Australia
Nora L. Lee United States
Mark Becker United States
Pedro Melo Portugal
Dagmar Waiblinger United Kingdom
Caroline Barakat Canada
Fan Tian United States
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Can Liu relative to Margaret Carroll Ireland Margaret Carroll's profile →
Citations per field
00.5×9.3×
Margaret Carroll · 1×
Citations per year

Countries citing papers authored by Can Liu

Since Specialization
Citations

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

Fields of papers citing papers by Can Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200977
2 201963
3 201530
4 201829
5 201429
6 201824
7 202119
8 201817
9 202214
10 201813
11 201813
12 202111
13 20218
14 20197
15 20196
16 20186
17 20206
18 20245
19 20204
20
LANDSCAPE SCALE FRACTAL ANALYSIS OF PATCH SHAPE IN THE VEGETATION OF THE BEIJING REGION
20004

About Can Liu

Can Liu is a scholar working on Clinical Psychology, Pediatrics, Perinatology and Child Health, Sociology and Political Science, Obstetrics and Gynecology and Health, having authored 34 papers that have together received 407 indexed citations. Recurring topics across this work include Migration, Health and Trauma (4 papers), Maternal and Perinatal Health Interventions (3 papers), Youth Education and Societal Dynamics (2 papers), Geology and Paleoclimatology Research (2 papers), Soil erosion and sediment transport (2 papers), Global Maternal and Child Health (2 papers), Maternal and fetal healthcare (2 papers) and Health disparities and outcomes (2 papers). The work is most often cited by research in Obstetrics and Gynecology (38 citations), Clinical Psychology (92 citations), Pediatrics, Perinatology and Child Health (65 citations), Neurology (28 citations) and Safety Research (27 citations). Can Liu has collaborated with scholars based in Sweden, United States and China. Frequent co-authors include Anders Hjern, Olof Stephansson, Elizabeth Wall‐Wieler, Mia Ahlberg, Marcelo L. Urquía, Suzan L. Carmichael, Yanqin Gao, R. Anne Stetler, Suping Wang and Hui Gao. Their work appears in journals such as PLoS ONE, BMC Pregnancy and Childbirth, Women s Health Issues, European Journal of Public Health and Journal of Affective Disorders.

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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