Feichen Shen

3.4k citations
67 papers · 2.0k indexed · 1 hit paper · h-index 21

Impact in

Papers in

Feichen Shen

65 papers receiving 2.0k citations

Hit Papers

Clinical information extraction applications: A literature review 2017 · 514 citations
5142017202620202023100200300400500

Peers

Feichen Shen
Comparison fields: 5 of 146
  • Health Informatics 148
  • Health Information Management 280
  • Artificial Intelligence 1.2k
  • Molecular Biology 965
  • Issues, ethics and legal aspects 14
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Citations per field
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Citations per year

Countries citing papers authored by Feichen Shen

Since Specialization
Citations

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

Fields of papers citing papers by Feichen Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Clinical information extraction applications: A literature review
Hit paper breakdown →
2017514
2 2019251
3 2018234
4 2020109
5 201879
6 201878
7 201937
8 202035
9 201334
10 202033
11 201829
12 201627
13
Integrating Structured and Unstructured EHR Data Using an FHIR-based Type System: A Case Study with Medication Data.
201826
14 201825
15 201924
16 201322
17
Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis.
201721
18 201920
19 201820
20 201920

About Feichen Shen

Feichen Shen is a scholar working on Health Information Management, Artificial Intelligence, Molecular Biology, Statistics, Probability and Uncertainty and Genetics, having authored 67 papers that have together received 2.0k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (52 papers), Topic Modeling (22 papers), Semantic Web and Ontologies (14 papers), Bioinformatics and Genomic Networks (13 papers), Natural Language Processing Techniques (11 papers), Genomics and Rare Diseases (10 papers), Machine Learning in Healthcare (9 papers) and Electronic Health Records Systems (6 papers). The work is most often cited by research in Health Informatics (148 citations), Health Information Management (280 citations), Artificial Intelligence (1.2k citations), Molecular Biology (965 citations) and Issues, ethics and legal aspects (14 citations). Feichen Shen has collaborated with scholars based in United States, China and India. Frequent co-authors include Hongfang Liu, Yanshan Wang, Liwei Wang, Sijia Liu, Majid Rastegar-Mojarad, Sunghwan Sohn, Naveed Afzal, Sungrim Moon, Yuqun Zeng and Saeed Mehrabi. Their work appears in journals such as Journal of Biomedical Informatics, Journal of the American Medical Informatics Association, Journal of Medical Internet Research, BMC Medical Informatics and Decision Making 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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