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Volume 20 Supplement 11

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

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 did not handle peer review on any articles that they have co-authored. The Supplement Editors declare that they have no other competing interests.

Virtual9-10 August 2020

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

Conference website

  1. The 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) provided a multidisciplinary forum for computational scientists and experimental biologists to share recent advances on all as...

    Authors: Li Shen, Xinghua Shi, Zhongming Zhao and Kai Wang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):342
  2. Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemia. The avalanche of healthcare data is accelerating precision and personalized medicine. Artificial intelligence and algo...

    Authors: Jiancheng Ye, Liang Yao, Jiahong Shen, Rethavathi Janarthanam and Yuan Luo
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):295
  3. Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and...

    Authors: Jacqueline Peng, Mengge Zhao, James Havrilla, Cong Liu, Chunhua Weng, Whitney Guthrie, Robert Schultz, Kai Wang and Yunyun Zhou
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):322
  4. Over 70% of Americans regularly experience stress. Chronic stress results in cancer, cardiovascular disease, depression, and diabetes, and thus is deeply detrimental to physiological health and psychological w...

    Authors: Russell Li and Zhandong Liu
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):285
  5. Age and time information stored within the histories of clinical notes can provide valuable insights for assessing a patient’s disease risk, understanding disease progression, and studying therapeutic outcomes...

    Authors: Judy Hong, Anahita Davoudi, Shun Yu and Danielle L. Mowery
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):338
  6. When an Out-of-Hospital Cardiac Arrest (OHCA) incident is reported to emergency services, the 911 agent dispatches Emergency Medical Services to the location and activates responder network system (RNS), if th...

    Authors: Gaurav Rao, Salimur Choudhury, Pawan Lingras, David Savage and Vijay Mago
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):313
  7. The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model ...

    Authors: Joseph Tassone, Peizhi Yan, Mackenzie Simpson, Chetan Mendhe, Vijay Mago and Salimur Choudhury
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):304
  8. The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer fr...

    Authors: Sundreen Asad Kamal, Changchang Yin, Buyue Qian and Ping Zhang
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):307
  9. Electrocardiogram (ECG) signal, an important indicator for heart problems, is commonly corrupted by a low-frequency baseline wander (BW) artifact, which may cause interpretation difficulty or inaccurate analys...

    Authors: Chao-Chen Chen and Fuchiang Rich Tsui
    Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):343

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)

Peer-review Terminology

  • The following summary describes the peer review process for this journal:

    Identity transparency: Single anonymized

    Reviewer interacts with: Editor

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

    More information is available here

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