Yuanfang Ren

969 citations
40 papers · 554 indexed · h-index 12
Topics
Bioinformatics and Genomic Networks (11 papers)Machine Learning in Healthcare (8 papers)Gene Regulatory Network Analysis (7 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaPLoS ONE
Partner nations
United StatesChinaItaly

In The Last Decade

Yuanfang Ren

35 papers receiving 544 citations

Peers

Yuanfang Ren
Comparison fields: 5 of 121
  • Artificial Intelligence 144
  • Cardiology and Cardiovascular Medicine 80
  • Cognitive Neuroscience 79
  • Health Informatics 77
  • Surgery 66
Replace Akhil Vaid with:
Akhil Vaid United States
Christian Bock Switzerland
Shuang Di Canada
Dean A. Bodenham Switzerland
Shinjini Kundu United States
Peter Weller United Kingdom
Sheng Yu China
Rishikesan Kamaleswaran United States
Wenqi Shi United States
Michael Moor Switzerland
Yuanfang Ren relative to Akhil Vaid United States Akhil Vaid's profile →
Citations per field
00.5×
Akhil Vaid · 1×
Citations per year

Countries citing papers authored by Yuanfang Ren

Since Specialization
Citations

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

Fields of papers citing papers by Yuanfang Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuanfang Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Yuanfang Ren. A scholar is included among the top collaborators of Yuanfang Ren based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yuanfang Ren. Yuanfang Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 0
4 2
5 2
6 1
7 3
8 5
9 21
10 0
11 4
12 31
13 9
14 49
15 2
16 10
17 54
18 31
19 1
20 17

About Yuanfang Ren

Yuanfang Ren is a scholar working on Health Informatics, Nephrology and Critical Care and Intensive Care Medicine, having authored 40 papers that have together received 554 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Machine Learning in Healthcare (8 papers) and Gene Regulatory Network Analysis (7 papers). The work is most often cited by research in Health Informatics (77 citations), Health Information Management (37 citations) and Nephrology (51 citations). Yuanfang Ren has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Yan Wu, Azra Bihorac, Tezcan Ozrazgat‐Baslanti, Benjamin Shickel, Tyler J. Loftus, Parisa Rashidi, Matthew M. Ruppert, Gilbert R. Upchurch, Tamer Kahveci and Shounak Datta. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología 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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