Analysis disease progression using data visualization

Enjie Liu
,
Youbing Zhao
,
Hui Wei
,
Eleni Kaldoudi
,
Stefanos Roumeliotis

Democritus University of Thrace

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

Abstract

Patients with chronic diseases are required to self-manage their conditions. Patients are normally advised to adapt to healthier life-style, and in the meantime to continuously monitor the relevant biomarkers. Recent technology advances in monitoring devices, such as activities waist bands and glucose sensors, made it much easier for the patients to monitor the level of activities and biomarkers in home environment. The aim is to assist patients in making informed decisions and the key feature to achieve will be based on thoroughly understand the meaning of the collected data with the help of known facts (knowledge). However, interpreting the meaning of the monitored data is a challenging task for an ordinary patient. Data visualization techniques play an important role in helping users to understand and interpret data via exploration. In this paper, we present data visualization diagrams that are used in CARRE project to help both medical professional and patients to understand the disease progressions.

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 877-882

Publication milestones

Published - 01/02/2018

Publication status

Published - 01/02/2018

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Print)

9781538630655

External Publication IDs

handle.net: 10547/623860
Scopus: 85047413503

Host publication title

2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)