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Volume 20 Supplement 4

Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019)

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. The Supplement Editors declare that they have no competing interests.

Auckland, New Zealand27 October 2019

Edited by Zhe He, Cui Tao, Jiang Bian and Rui Zhang

Conference website

  1. In this introduction, we first summarize the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019) held on October 26, 2019 in conjunction with the 18th International Semant...

    Authors: Zhe He, Cui Tao, Jiang Bian and Rui Zhang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):315
  2. Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new know...

    Authors: Anderson Rossanez, Julio Cesar dos Reis, Ricardo da Silva Torres and Hélène de Ribaupierre
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):314
  3. Leveraging graphs for machine learning tasks can result in more expressive power as extra information is added to the data by explicitly encoding relations between entities. Knowledge graphs are multi-relation...

    Authors: Gilles Vandewiele, Bram Steenwinckel, Filip De Turck and Femke Ongenae
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):191
  4. To reduce cancer mortality and improve cancer outcomes, it is critical to understand the various cancer risk factors (RFs) across different domains (e.g., genetic, environmental, and behavioral risk factors) a...

    Authors: Hansi Zhang, Yi Guo, Mattia Prosperi and Jiang Bian
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):292
  5. Semantic web technology has been applied widely in the biomedical informatics field. Large numbers of biomedical datasets are available online in the resource description framework (RDF) format. Semantic relat...

    Authors: Li Zhang, Jiamei Hu, Qianzhi Xu, Fang Li, Guozheng Rao and Cui Tao
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):283
  6. Previously, we introduced our Patient Health Information Dialogue Ontology (PHIDO) that manages the dialogue and contextual information of the session between an agent and a health consumer. In this study, we ...

    Authors: Muhammad Amith, Rebecca Z. Lin, Licong Cui, Dennis Wang, Anna Zhu, Grace Xiong, Hua Xu, Kirk Roberts and Cui Tao
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):259
  7. Treatment effect prediction (TEP) plays an important role in disease management by ensuring that the expected clinical outcomes are obtained after performing specialized and sophisticated treatments on patient...

    Authors: Jiebin Chu, Wei Dong, Jinliang Wang, Kunlun He and Zhengxing Huang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):139
  8. Emotions after surviving cancer can be complicated. The survivors may have gained new strength to continue life, but some of them may begin to deal with complicated feelings and emotional stress due to trauma ...

    Authors: Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He and Xia Hu
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 4):254

Annual Journal Metrics

  • Citation Impact
    3.298 - 2-year Impact Factor (2021)
    3.894 - 5-year Impact Factor (2021)
    1.387 - SNIP (Source Normalized Impact per Paper)
    0.833 - SJR (SCImago Journal Rank)

    Speed
    43 days to first decision for all manuscripts (Median)
    88 days to first decision for reviewed manuscripts only (Median)

    Usage 
    2,056,778 Downloads (2021)
    1,628 Altmetric mentions (2021)

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