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Life style related risk association mining

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

IoT application in health care provides ways to monitor and collect health related biomarkers, in particular, life-style related data, by recording and analyzing long-Term data, to provide insight to patients' status. In order to make most use of this application, linking the collected patients' data with a disease predictive model will generate a personalized disease progression and predictions. It is also important to understand one's health risks in order to benefit from new research about specific diseases and plan for preventive monitoring. Risk factors for a disease are results of various medical researches. In this paper, we propose an approach for risk factor selection and mining.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 79-84

Publication milestones

  • Published - 25/04/2019

Publication status

Published - 25/04/2019

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Print)

9781538691311

External Publication IDs

  • handle.net: 10547/623819
  • Scopus: 85065542311

Host publication title

2018 International Conference on Internet of Things, Embedded Systems and Communications (IINTEC)

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