Xiaochen Ma

538 citations
25 papers · 171 · h-index 8

Impact in

Papers in

Xiaochen Ma

24 papers receiving 168 citations

Peers

Xiaochen Ma
Comparison fields: 5 of 63
  • Oncology 67
  • Cancer Research 30
  • Reproductive Medicine 14
  • Immunology 34
  • Hepatology 10
Replace Silvia Chiellino with:
Silvia Chiellino Italy
Eva Hulstaert Belgium
Huini Wu China
Lucian Miron Romania
Hecheng Li China
Shaocheng Lyu China
Qingyi Wang China
Maurizio Pinamonti Italy
Şahin Laçin Türkiye
Hong‐Lei Guo China
Xiaochen Ma relative to Silvia Chiellino Italy Silvia Chiellino's profile →
Citations per field
00.5×3.4×
Silvia Chiellino · 1×
Citations per year

Countries citing papers authored by Xiaochen Ma

Since Specialization
Citations

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

Fields of papers citing papers by Xiaochen Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202235
2 202417
3 202214
4 202113
5 201412
6
[A case-control study on the association between folate and cervical cancer].
200612
7 20208
8 20238
9 20207
10 20217
11 20236
12 20216
13 20234
14 20224
15 20233
16 20252
17 20212
18 20242
19 20242
20 20242

About Xiaochen Ma

Xiaochen Ma is a scholar working on Oncology, Molecular Biology, Pulmonary and Respiratory Medicine, Surgery and Immunology, having authored 25 papers that have together received 171 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (3 papers), Gallbladder and Bile Duct Disorders (3 papers), Colorectal Cancer Treatments and Studies (3 papers), Cancer, Lipids, and Metabolism (2 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers), Power System Optimization and Stability (2 papers), Smart Grid and Power Systems (2 papers) and Transportation Planning and Optimization (2 papers). The work is most often cited by research in Oncology (67 citations), Cancer Research (30 citations), Reproductive Medicine (14 citations), Immunology (34 citations) and Hepatology (10 citations). Xiaochen Ma has collaborated with scholars based in China and Netherlands. Frequent co-authors include Jinhong Chen, Jiahao Han, Xin Zheng, Yitong Li, Baorui Tao, Ruxin Chen, Zixuan Gao, Chenhe Yi, Chu Zhang and Yuying Cheng. Their work appears in journals such as International Journal of Colorectal Disease, China CDC Weekly, Journal of Surgical Oncology, Surgery and Transportation Research Part E Logistics and Transportation Review.

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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