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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

    Content type: Introduction

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

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  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

    Content type: Research

    Published on:

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