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Volume 21 Supplement 5

Informatics and machine learning methods for health applications (part two)

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. Supplement Editors were not involved in the peer review of any article that they co-authored. The Supplement Editors declare that they have no other competing interests.

Virtual9-10 August 2020

Conference website 

Edited by Li Shen, Xinghua Mindy Shi, Zhongming Zhao and Kai Wang.

  1. Sepsis is a highly lethal and heterogeneous disease. Utilization of an unsupervised method may identify novel clinical phenotypes that lead to targeted therapies and improved care.

    Authors: Menghan Ding and Yuan Luo
    Citation: BMC Medical Informatics and Decision Making 2021 21(Suppl 5):95
    Content type: Research Published on:
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Annual Journal Metrics

  • 2022 Citation Impact
    3.5 - 2-year Impact Factor
    3.9 - 5-year Impact Factor
    1.384 - SNIP (Source Normalized Impact per Paper)
    0.940 - SJR (SCImago Journal Rank)

    2023 Speed
    37 days submission to first editorial decision for all manuscripts (Median)
    213 days submission to accept (Median)

    2023 Usage 
    2,588,758 downloads
    2,443 Altmetric mentions 

Peer-review Terminology

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    Identity transparency: Single anonymized

    Reviewer interacts with: Editor

    Review information published: Review reports. Reviewer Identities reviewer opt in. Author/reviewer communication

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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