Analysis disease progression using data visualization
| dc.contributor.author | Liu, Enjie | en |
| dc.contributor.author | Zhao, Youbing | en |
| dc.contributor.author | Wei, Hui | en |
| dc.contributor.author | Kaldoudi, Eleni | en |
| dc.contributor.author | Roumeliotis, Stefanos | en |
| dc.date.accessioned | 2020-02-21T14:18:24Z | |
| dc.date.available | 2020-02-21T14:18:24Z | |
| dc.date.issued | 2018-02-01 | |
| dc.identifier.citation | Liu E, Zhao Y, Wei H, Kaldoudi E, Roumeliotis S (2018) 'Analysis disease progression using data visualization', 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, Institute of Electrical and Electronics Engineers Inc.. | en |
| dc.identifier.isbn | 9781538630655 | |
| dc.identifier.doi | 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.135 | |
| dc.identifier.uri | http://hdl.handle.net/10547/623860 | |
| dc.description.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. | |
| dc.language.iso | en | en |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en |
| dc.relation.url | https://ieeexplore.ieee.org/document/8276854 | en |
| dc.subject | Internet of Things | en |
| dc.subject | visual analytics | en |
| dc.subject | risk factors | en |
| dc.subject | cata visulisation | en |
| dc.title | Analysis disease progression using data visualization | en |
| dc.type | Conference papers, meetings and proceedings | en |
| dc.contributor.department | University of Bedfordshire | en |
| dc.contributor.department | University of Thrace | en |
| dc.date.updated | 2020-02-21T14:10:47Z | |
| html.description.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. |