Analysis disease progression using data visualization

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

doi:10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135

Analysis disease progression using data visualization

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

Institute for Research in Applicable Computing (IRAC)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	nan
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	877-882
ISBN (Print)	9781538630655
DOIs	https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135
Publication status	Published - 1 Feb 2018
Event	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) - Exeter Duration: 21 Jun 2017 → 23 Jun 2017

Conference

Conference	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)
City	Exeter
Period	21/06/17 → 23/06/17
Other	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) (21/06/2017-23/06/2017, Exeter)

Keywords

Data visulisation
Internet of things
risk factors
visual analytics

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10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135

https://ieeexplore.ieee.org/document/8276854

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Cite this

@inproceedings{d314e03793fa4968b1b8ccd9479797ab,

title = "Analysis disease progression using data visualization",

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.",

keywords = "Data visulisation, Internet of things, risk factors, visual analytics",

author = "Enjie Liu and Youbing Zhao and Hui Wei and Eleni Kaldoudi and Stefanos Roumeliotis",

year = "2018",

month = feb,

day = "1",

doi = "10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135",

language = "English",

isbn = "9781538630655",

pages = "877--882",

booktitle = "nan",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "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) ; Conference date: 21-06-2017 Through 23-06-2017",

}

Liu, E, Zhao, Y, Wei, H, Kaldoudi, E & Roumeliotis, S 2018, Analysis disease progression using data visualization. in nan. Institute of Electrical and Electronics Engineers Inc., pp. 877-882, 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), Exeter, 21/06/17. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135

TY - GEN

T1 - Analysis disease progression using data visualization

AU - Liu, Enjie

AU - Zhao, Youbing

AU - Wei, Hui

AU - Kaldoudi, Eleni

AU - Roumeliotis, Stefanos

PY - 2018/2/1

Y1 - 2018/2/1

N2 - 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.

AB - 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.

KW - Data visulisation

KW - Internet of things

KW - risk factors

KW - visual analytics

U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135

DO - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135

M3 - Conference contribution

SN - 9781538630655

SP - 877

EP - 882

BT - nan

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 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)

Y2 - 21 June 2017 through 23 June 2017

ER -

Analysis disease progression using data visualization

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