Xiaoying Liu

1.1k citations
32 papers · 632 · h-index 15

Impact in

Papers in

Xiaoying Liu

30 papers receiving 625 citations

Peers

Xiaoying Liu
Comparison fields: 5 of 93
  • Health Informatics 9
  • Oncology 150
  • Epidemiology 165
  • Hepatology 37
  • Reproductive Medicine 35
Replace Ji Young Park with:
Ji Young Park South Korea
Jin Zhou China
Chee Leong Cheng Singapore
Lan Peng United States
Cong Xu China
Zhiqiao Zhang China
Hang Zhou China
Panwen Tian China
Shaobo Hu China
Kaiqian Zhou China
Xiaoying Liu relative to Ji Young Park South Korea Ji Young Park's profile →
Citations per field
00.5×1.5×2.3×
Ji Young Park · 1×
Citations per year

Countries citing papers authored by Xiaoying Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoying Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202076
2 201474
3 201863
4 201549
5 202044
6 202044
7 202134
8 202029
9 202228
10 200428
11 201825
12 202122
13 201918
14 201917
15 201815
16 202314
17
Analysis of gene expression in hepatitis B virus transfected cell line induced by interferon.
200311
18 202410
19 20226
20 20225

About Xiaoying Liu

Xiaoying Liu is a scholar working on Epidemiology, Molecular Biology, Surgery, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 32 papers that have together received 632 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (4 papers), Hepatitis B Virus Studies (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), Neuroendocrine Tumor Research Advances (2 papers), Diet, Metabolism, and Disease (2 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers) and Immune Response and Inflammation (2 papers). The work is most often cited by research in Health Informatics (9 citations), Oncology (150 citations), Epidemiology (165 citations), Hepatology (37 citations) and Reproductive Medicine (35 citations). Xiaoying Liu has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Arief A. Suriawinata, Bing Ren, Louis Vaickus, Mikhail Lisovsky, Saeed Hassanpour, Jason Wei, Naofumi Tomita, Anne S. Henkel, Kristy A. Anderson and Richard M. Green. Their work appears in journals such as JAMA Network Open, Clinical Epigenetics, Journal of Cutaneous Pathology, American Journal Of Pathology 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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