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Related Experiment Video

Updated: Feb 2, 2026

BioMEMS: Forging New Collaborations Between Biologists and Engineers
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SCOSY: A Biomedical Collaboration Recommendation System.

Jorge Guerra, Wei Quan, Kai Li

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |November 17, 2018
    PubMed
    Summary
    This summary is machine-generated.

    Schosy enhances scientific collaboration by recommending researchers based on their work and network. This system aids both researchers and non-technical users in finding relevant collaborators more efficiently.

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    Area of Science:

    • Biomedical Informatics
    • Bibliometrics
    • Scientific Collaboration

    Background:

    • Identifying relevant scientific articles and collaborators is challenging.
    • Recommendation systems for scientific collaboration are underutilized in healthcare.

    Purpose of the Study:

    • To develop Schosy, a system addressing the practice gap in healthcare collaboration.
    • To enhance the discovery of scientific collaborators for researchers and non-technical users.

    Main Methods:

    • Collected publication metadata from PubMed.
    • Combined Collaborative Filtering and Content-Based Filtering techniques.
    • Utilized Latent Dirichlet Allocation (LDA) for topic modeling.

    Main Results:

    • Developed a system recommending collaborators based on work, network, and MeSH terms.
    • Provided an interpretable latent structure for collaborators and databases.
    • Improved the process of finding scientific collaborators.

    Conclusions:

    • Schosy effectively recommends collaborators by analyzing publication data and research networks.
    • The system enhances collaboration discovery for diverse user groups within biomedical fields.