Yefeng Wang

801 citations
47 papers · 585 · h-index 13

Impact in

Papers in

Yefeng Wang

41 papers receiving 565 citations

Peers

Yefeng Wang
Comparison fields: 5 of 111
  • Health Information Management 32
  • Artificial Intelligence 224
  • Molecular Biology 235
  • Health Informatics 4
  • Toxicology 8
Replace Leon Weber with:
Leon Weber Germany
Saber A. Akhondi Netherlands
Yankang Jing United States
P. K. Krishnan Namboori India
Honglei Liu China
Fergus Imrie United Kingdom
Francisco Cedrón Spain
Charles Tapley Hoyt Germany
Swetha Dhamercherla India
Zengjian Liu China
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Citations per field
00.5×7.2×
Leon Weber · 1×
Citations per year

Countries citing papers authored by Yefeng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yefeng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201565
2 200956
3 201149
4 200945
5
An automated system for conversion of clinical notes into SNOMED clinical terminology
200743
6 201638
7 200831
8 202431
9 202426
10 201917
11 202214
12 201912
13
Developing SNOMED CT Subsets from Clinical Notes for Intensive Care Service
200812
14 202211
15
Automatic Mapping Clinical Notes to Medical Terminologies
200611
16
Biomedical named entity recognition system
200511
17 201910
18 20079
19 20238
20
Term Coverage of Dietary Supplements Ingredients in Product Labels.
20168

About Yefeng Wang

Yefeng Wang is a scholar working on Molecular Biology, Artificial Intelligence, Surgery, Pathology and Forensic Medicine and Cardiology and Cardiovascular Medicine, having authored 47 papers that have together received 585 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (13 papers), Natural Language Processing Techniques (8 papers), Semantic Web and Ontologies (7 papers), Topic Modeling (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Nutrition, Genetics, and Disease (2 papers), Cardiac Arrhythmias and Treatments (2 papers) and Spinal Cord Injury Research (2 papers). The work is most often cited by research in Health Information Management (32 citations), Artificial Intelligence (224 citations), Molecular Biology (235 citations), Health Informatics (4 citations) and Toxicology (8 citations). Yefeng Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jon Patrick, David A. Blank, Victor N. Nemykin, Min Li, Graeme Miller, Eranda Maligaspe, Yuriy V. Zatsikha, Anatolii A. Purchel, Rui Zhang and Jiang Bian. Their work appears in journals such as Medicine, Frontiers in Genetics, Frontiers in Pediatrics, BMC Medical Informatics and Decision Making and Natural Product Communications.

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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